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Computer Vision Intern — Data Labeling & Annotation Type: Internship / Temporary Duration: 6 months - 12 months What You'll Gain Exposure to the full CV pipeline, from raw data to deployed model Mentorship from CV engineers working on production systems Hands-on experience with YOLO, PyTorch, and modern annotation workflows Concrete portfolio work — datasets, scripts, and model contributions — that translates directly to future ML/CV roles What You'll Do Annotate images and video for object detection (bounding boxes), segmentation (polygons/masks), and classification Help refine labeling schemas and class taxonomies as edge cases come up Write Python scripts to convert between annotation formats, validate label integrity, and generate dataset statistics QA labels and surface systematic errors or ambiguous cases Run baseline YOLO training experiments to evaluate dataset quality and identify labeling gaps Document conventions and edge-case decisions Required Pursuing a degree in CS, EE, AI/ML, or related field Working knowledge of Python and common CV libraries (NumPy, OpenCV) Attention to detail and patience for precision work Nice to Have Hands-on experience with YOLO Familiarity with PyTorch, segmentation masks, or model-assisted labeling workflows

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About Us:AltaML is a leading North American applied AI company with extensive experience in building and operationalizing AI software solutions. We are a company like no other – we believe in making small bets, failing fast, and being better together. We are looking for creative problem-solvers who obsess about the customer to find wins across different industries. We don’t hire for fit; we hire to add. We are looking for people who play our core values of being: Agile, Gritty Humble, and Happy. If you’re passionate about AI/ML, thrive in a dynamic environment, and want to work with a diverse team of wickedly smart people, we want to hear from you!We are looking for a Full Stack Software Engineer who builds software in an AI-native way — someone who treats Claude and the latest agentic coding tools as a core part of their craft, not a novelty. In this role, you will contribute to the technical delivery of ML-powered applications across cloud services, APIs, and modern front-end frameworks, with Claude Code, the Claude API, and agentic workflows woven into how you design, build, and ship. You will be an active contributor within your project pod, shipping features end-to-end, participating in technical design discussions, and growing your ability to translate business requirements into well-engineered solutions. You will take ownership of your work — writing clean, reviewable code, contributing to shared internal frameworks, and continuously developing your fluency with AI-assisted development. You will thrive in this role if you are a builder who leans on Claude Code to move fast without cutting corners. You write clear specs, review AI-generated code critically, and know when to delegate to an agent versus when to handcraft. You are curious about where LLMs fit (and where they don’t), and you bring a practical, evidence-based instinct to that question.What You'll Do:Full Stack Feature Delivery Implement features end-to-end across front-end, back-end, and cloud infrastructure layers, taking ownership from design through deployment Build and integrate RESTful APIs and cloud-hosted services, primarily on Azure, following established architecture patterns and security standards Develop front-end components using modern JavaScript/TypeScript frameworks, with attention to usability, performance, and maintainability Write unit, integration, and API tests as a standard part of delivery — not an afterthought — using frameworks appropriate to the stack (xUnit, Pytest, Postman, or similar) Use Docker for local development, environment parity, and containerized deployments Manage work in Git with clean branching, meaningful commit history, and effective collaboration with AI agents in the same workflow LLM Feature Development Build features that incorporate LLM calls via the Claude API or Azure OpenAI, including prompt design, context management, response handling, and cost-aware API usage Implement RAG components and tool integrations as part of product features, working within established architecture patterns and contributing to their evolution Write evaluation harnesses for LLM-powered features: regression tests for prompt behaviour, output quality checks, and agent tool use validation Document LLM feature behaviour clearly: what the system does, what it does not do, known failure modes, and the guardrails in place Develop growing awareness of when LLM-in-the-loop is the right architecture decision versus a conventional software approach — and contribute that perspective in design discussions Technical Design & Problem-Solving Participate actively in epic-level and feature-level design discussions, contributing well-reasoned proposals backed by research or prototype evidence Use Claude to accelerate technical research: explore design alternatives, evaluate libraries, and investigate unfamiliar domains quickly — then synthesize findings into a clear recommendation Identify and flag technical risks within your work scope early, with enough supporting detail for the tech lead or architect to make an informed decision Produce clear technical documentation: decision records, implementation notes, and design summaries that a future team member can act on AI-Native Development Use Claude Code and AI-assisted development tools (Cursor, GitHub Copilot, and similar) as a standard part of the engineering workflow — for prototyping, code generation, refactoring, documentation, and debugging Write clear, well-structured prompts and development specs that enable AI agents to produce useful, reviewable output — not vague instructions that generate noise Review AI-generated code with the same rigour as human-authored code: check for correctness, edge cases, security issues, and maintainability before merging Develop growing fluency in agentic development patterns: structuring repos for agent navigation, decomposing tasks into agent-friendly units, and knowing when human authorship is the right call Contribute to internal discussions on AI tooling effectiveness — share what is working, what isn’t, and help refine the team’s approach Collaboration & Growth Participate in code reviews constructively — give specific, actionable feedback and incorporate peer feedback into your own work without defensiveness Collaborate closely with ML engineers, data engineers, and product managers within the pod, understanding adjacent work well enough to minimize integration friction Contribute reusable components, utilities, and internal skills to AltaML’s shared libraries Engage in sprint ceremonies, stand-ups, and retrospectives as an active team member — raise blockers early, communicate progress clearly, and contribute to continuous improvement Proactively seek feedback from peers and tech leads to accelerate your own growth toward senior-level ownership and technical leadership What You Bring: Degree or equivalent work experience in Computer Science, Software Engineering, or a related technical discipline 3–5 years of professional full stack development experience, with a track record of shipping production features end-to-end Hands-on, daily-driver experience using Claude (Claude Code, claude.ai, or the Claude API), Cursor, or GitHub Copilot for real software engineering work — not just occasional use Strong working experience with cloud services, ideally Azure (Functions, App Service, Blob Storage, Azure OpenAI, or similar) Proficiency in a modern object-oriented language — C#, Python, TypeScript, or equivalent — with a clear point of view on writing clean, maintainable code Experience building and consuming RESTful APIs and integrating third-party services Solid front-end experience with a modern JavaScript/TypeScript framework (React, Vue, Angular, or similar) Experience writing unit and API tests as a standard part of delivery (xUnit, Pytest, Postman, or similar) Comfortable with Docker for local development and containerized deployments Proficiency with Git, including working effectively in a branch-based workflow alongside AI agents Experience working in an Agile environment with iterative delivery cycles Strong written and verbal communication skills — able to articulate technical decisions clearly to peers and participate confidently in client-facing discussions   Nice to Have's: Experience integrating LLM APIs (Claude, OpenAI, Azure OpenAI) into product features, including prompt design and cost management Exposure to RAG architectures, vector databases, or tool-augmented LLM workflows Familiarity with agentic frameworks (LangChain, LangGraph, Autogen, or similar) Experience writing evaluation harnesses or regression tests for LLM-powered features Exposure to CI/CD pipelines and automated deployment workflows (Azure DevOps, GitHub Actions, or similar) Prior experience in a consulting, applied AI, or client-delivery environment Contributions to open-source projects or internal platforms 90,000 - 110,000 a yearResponsible AI (RAI)AltaML employees, contractors, and associates must be trained and well-versed in the importance of Responsible AI and empowered to enact RAI principles by developing and deploying AI solutions. They should also be empowered to raise and escalate RAI concerns as required. AltaML is responsible for elevating public discourse and awareness of AI through open, transparent communications with the broader public. Equal OpportunitiesAltaML is dedicated to fostering a safe, diverse, and inclusive workplace as an equal-opportunity employer. We welcome applications from qualified individuals of all backgrounds, encompassing ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and educational backgrounds. If you are invited for an interview and require accommodations during the interview process, please don’t hesitate to let us know. AltaML acknowledges that its head office is located on Treaty 6 territory, and respects the histories, languages, and cultures of First Nations, Métis, Inuit, and all First Peoples of Canada, whose presence continues to enrich our vibrant community. We Look for A-Players Who:- Express our core values- Are hungry for knowledge- Want to learn new skills- Are respectful- Collaborate with others across the whole company- Share knowledge with coworkers- Educate and promote AI and ML concepts both internally and externally- Have a high work ethic and are self-motivated Our Perks:🌴Uncapped Vacation - For all full time, permanent employees. Seriously, take the time you need - when you need it.🚀Make an Impact - Witness the impact your work contribution has on the success of our company.👩🏿‍💻Working with PhD and Master Level Colleagues - Endless conversations around the latest in Machine Learning and Applied AI.🩺Competitive Benefits - For all full time, permanent employees. 🏢 Office as a Resource -  Hybrid work environment with state-of-the-art office spaces that ignite collaboration.⚡Big Slack Energy - IYKYK. Our Culture:You will be working in a high-paced environment focused on creating unique ML solutions to problems across multiple industries to generate impactful value. You will be working at a company with employees who have multiple years of industrial and academic experience in data science, software engineering, product development, and machine learning fields.  You will be able to experience a collaborative company culture, which means we believe in working hard, getting the job done, and enjoying the group social on Fridays. You’ll also get flexibility in where you work, what hours you work, how much vacation you take, and what you wear. We expect hard work but respect work/life balance. Core Values:At AltaML, we are driven by our core values. We believe that by embodying these values in everything we do, we will exceed our customer’s expectations while creating a positive and empowering work environment for our team members. We are dedicated to living our values and strive to make them the foundation for our success.  Gritty - We are entrepreneurial, determined, and resilient, pushing through challenges to achieve our goals. Agile - We make decisions based on “little bets” creating a safe space to take risks. We embrace an interactive process, allowing ideas to fail quickly or be scaled iteratively. Together, we continuously refine and improve our approach to reach the desired outcome.  Humble - We listen to data, embrace new ideas, admit limitations and take ownership to solve problems. We constantly push ourselves to improve and excel.   Happy - We ignite passion and purpose by fostering a dynamic work environment. We encourage tap dancing to work, common sense over rules, empowering team members to find joy in their contributions, and being your authentic self.

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We are looking for the bestAbout Us42dot은 소프트웨어와 AI로 모빌리티 문제를 해결하기 위해 노력하는 모빌리티 AI 기업입니다. 현대자동차그룹 글로벌 소프트웨어 센터로서, 42dot은 소프트웨어 정의 차량 개발을 선도하며 미래 모빌리티를 개척하고 있습니다.LLM Engineer (LLM Evaluation)는 대규모 언어 모델(LLM)의 성능을 신뢰성 있게 평가하고, 평가 결과를 기반으로 모델 품질을 지속적으로 개선할 수 있는 평가 체계와 플랫폼을 구축합니다.빠르게 변화하는 LLM 환경 속에서 benchmark dataset, evaluation protocol, automation pipeline을 설계하여 모델의 품질과 안정성을 지속적으로 향상시키고, 실서비스 수준의 검증 체계를 운영하는 데 기여합니다.또한 Kubernetes 기반 환경에서 Argo Workflows 및 MLflow를 활용하여 모델 평가–실험 관리–배포 검증까지 이어지는 end-to-end evaluation workflow를 구축하고, 반복 가능하고 재현성 있는 평가 환경을 고도화합니다.ResponsibilitiesLLM Evaluation & Benchmark 설계LLM 성능 평가를 위한 벤치마크 데이터셋 구축 및 평가 지표(Human/LLM-based) 설계공정한 모델 비교를 위한 평가 프로토콜 수립 및 재현성(Reproducibility) 확보Evaluation Automation 및 Workflow 연동Argo Workflows, MLflow 기반의 평가 자동화 환경 구축 및 ML 파이프라인 통합모델 배포 시 성능 저하(Regression) 자동 감지 및 알림 체계 설계Model Quality Validation 및 운영 고도화반복 가능한 평가 워크플로우를 통한 대규모 모델 품질 및 안정성 검증평가 결과를 바탕으로 한 지속적인 모델 품질 개선 프로세스 운영QualificationsLLM 학습 또는 평가 관련 분야 3년 이상 경력Deep Learning 또는 NLP 관련 연구 및 개발 경험LLM evaluation framework 사용 경험 (lm-eval, HELM, OpenAI Evals 등)Python 기반 서비스 개발 경험 (async/비동기 처리 포함)실험 관리 및 reproducibility에 대한 이해모델 평가 및 validation workflow 설계 경험동료와의 원활한 협업 능력Preferred QualificationsKubernetes 및 컨테이너 기반 환경 개발 경험대규모 데이터 처리 또는 pipeline 설계 경험GPU 기반 분산 inference 또는 대규모 모델 평가 경험Datadog, Prometheus 등을 활용한 모니터링 구축 경험MLflow, Argo Workflows 기반 ML workflow 운영 경험GPU 클러스터 기반 evaluation pipeline 설계 및 운영 경험LLM 품질 평가 자동화 및 운영 경험Interview Process서류전형 - 코딩테스트 - 화상면접 (1시간 내외) - 대면 혹은 화상면접 (3시간 내외) - 최종합격전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.Additional Information이력서 제출 시 주민등록번호, 가족관계, 혼인 여부, 연봉, 사진, 신체조건, 출신 지역 등 채용절차법상 요구 금지된 정보는 제외 부탁드립니다.모든 제출 파일은 30MB 이하의 PDF 양식으로 업로드를 부탁드립니다. (이력서 업로드 중 문제가 발생한다면 지원하시고자 하는 포지션의 URL과 함께 이력서를 recruit@42dot.ai으로 전송 부탁드립니다.)인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다.국가보훈대상자 및 취업보호 대상자는 관계법령에 따라 우대합니다.장애인 고용 촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.42dot은 의뢰하지 않은 서치펌의 이력서를 받지 않으며, 요청하지 않은 이력서에 대해 수수료를 지불하지 않습니다.3개월의 수습기간이 적용될 수 있습니다.※ 지원 전 아래 내용을 꼭 확인해 주세요.42dot이 일하는 방식, 42dot Way 보러가기 →42dot만의 업무몰입 프로그램, Employee Engagement Program 보러가기 →

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Imagine having the power to stress-test an entire power grid against a hurricane or thunderstorm before the clouds even gather. That is the reality we are creating at Neara.We use advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents, this helps asset owners understand their biggest challenges and bring the most viable solutions to life across millions of kilometres of infrastructure.By simulating extreme weather and structural stress at a network-wide scale, we empower the world’s largest utilities to pinpoint risks, optimise investments and build a more resilient global energy future.Our team is a collection of brilliant minds who are fanatical about making a tangible difference in the real world, utilising AI and machine learning to accelerate everything from data classification to complex scenario analysis. We have built a special culture where innovation thrives because everyone owns the mission and we need smart, creative people to help us scale this impact to every corner of the globe.Data ScientistAs a Data Scientist, you will analyze a rich array of real-world data to inform our digital twin model of the electric grid, including topography, LIDAR, imagery, vegetation, structural loading, and electrical connectivity. Your work will drive product direction with high visibility, highlight grid expansion opportunities, identify aging and risky infrastructure, and help our customers understand where to build and invest. Working alongside ML Engineers and product-facing engineering teams, your ideas will ultimately take shape as new product features that expand what Neara is capable of doing, and as new infrastructure buildouts for the energy grid itself.What You Will Do:Model accurate digital twin electric networks from imperfect data using AI, deep learning, and classical ML algorithms.Surface meaningful analytics and metrics such as wildfire risk that help guide customer buildout of electrical infrastructure.Advise the company on what our data says and use that understanding to inform Neara’s strategy.Conduct experiments and A/B tests to improve our modeling of the grid.QA and improve our predictive models; identify data issues such as distribution drift, overfitting, or test set leakage.Craft scalable data pipelines to work with a variety of data sources, including LiDAR, aerial photography, photogrammetry and GIS.Mentor others in best practices for model training, data analytics, and building data-driven products.Who You Are:A data scientist, ML scientist, data engineer, or similar with 3-6 years of experience at technical, data-driven companies operating in complex environments. Geospatial data or power grid experience are a plus.You have a strong intuition for data with good communication skills and experience sharing your findings with customers and senior leaders.Demonstrated experience with AI and Machine Learning and a keen intuition for data modeling.Experience translating your models into both experiments and deployable software.Proficiency in data storage and ETL technologies, such as Parquet, Databricks, Snowflake, PostgreSQL, Spark, and DynamoDB.Comfort working in an AWS cloud environment.Excellent problem-solving skills as applied to new domains.Ability to work effectively asynchronously and cross-functionally on novel, cutting-edge problems.Ability to own problems and proactively approach challenges.Prior experience in the energy industry is a plus.What We Offer:Work with a sophisticated, multi-modal data stack, including LiDAR, satellite imagery, and physics-enabled digital twins, to solve high-stakes engineering problems that most data scientists only see in theory.Your models will directly prevent wildfires and mitigate disaster risks across millions of kilometers of infrastructure, moving beyond "digital metrics" to harden the real-world energy grid.You won't just build models; you’ll advise the company on data strategy and see your experiments evolve into core product features that dictate how the world’s largest utilities invest.We offer a highly competitive compensation package with a significant equity component, ensuring you are a true stakeholder in our mission and benefit directly from the company’s rapid global scale.

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About the Science TeamAt the heart of Maki People, the Science team is shaping the future of hiring through innovation, rigour, and collaboration. Led by our Head of Science, Aiden Loe, and working closely with our COO, Paul-Louis Caylar, this team drives the development of high-quality content that sets our platform apart.We don’t just create and validate assessments—we innovate. Our work spans:Expanding a cutting-edge library of tests and tools.Designing bespoke activities and experiences for clients.Evaluating and refining AI-driven scoring algorithms and large language models (LLMs) to ensure fairness, accuracy, and transparency.Leveraging psychometric expertise to build reliable, valid, and impactful assessments.Developing tools that analyse candidate and job data to predict performance and potential with precision.Supporting clients in using assessment data to optimise their workforce strategies, from talent acquisition to development and retention.Leading original studies to explore emerging psychological and technological trends and sharing insights through publications, presentations, and client reports.Collaborating with regulatory bodies and industry leaders to establish new standards in ethical AI use and hiring practices.Equipping internal teams and clients with the knowledge and skills needed to understand and apply psychological and AI-driven insights effectively.As Maki continues to grow, the Science team is central to understanding user experiences, refining assessments, and driving broader adoption—all while upholding the highest scientific standards.Your impact as a psychometrician intern will go beyond day-to-day responsibilities— you’ll be a key partner in shaping the future of recruitment while driving exceptional outcomes for our clients.Psychometrics & AI Assessment InternAbout the RoleYou'll help design, validate, and improve AI-powered assessments, working at the crossover between psychometrics and machine learning. Your work will directly shape how Maki evaluates candidates at scale.Day-to-day you'll be:Building and validating psychometric assessments designed for AI integrationRunning analyses on item quality, fairness, reliability, and scoring accuracyHelping develop and refine automated scoring algorithmsExploring how LLMs can be used to generate and evaluate assessment contentTranslating findings into clear insights for clients and internal teamsContributing to research reports and potentially academic publicationsWhat We're Looking ForStudying towards or recently completed an MSc or PhD in Psychometrics, Data Science, Psychology, or a related fieldSolid grounding in psychometric methods (IRT, CFA, CTT, SEM)Some experience with AI/ML or LLMs in an assessment context is a plusComfortable with R or Python and statistical software (SPSS, Mplus, or similar)Strong research and writing skillsAble to work across teams and explain technical findings to non-technical audiencesApplication ProcessStage 1 - Screening assessment (20 mins)Stage 2 - Hiring manager interview (45 min)Stage 3 - Power skill assessment with our AI agent (15 min)Stage 4 - Deep-dive technical interview (60 min)

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Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans — including many of the top 20 and representing more than 270 million lives — Machinify brings together a fully configurable, content-rich, AI-powered platform along with best-in-class expertise. We're constantly reimagining what's possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. The Role We're building production-grade agentic systems that audit medical claims end-to-end — reading raw medical records, reasoning over coding and clinical guidelines, and producing defensible findings that hold up to clinical and regulatory review. Reaching human-expert accuracy on noisy, long-context documents is one of the hardest unsolved problems in applied AI, and the field is moving weekly. We're hiring an L4 AI Engineer who can step into an ambiguous problem, design an agent system from scratch, and ship it. You won't be plugging into someone else's architecture — you'll be deciding what the architecture should be. What You'll Do - Design agent systems from first principles. Decide the loop, the tools, the context strategy, the evaluation harness. Choose between single-agent and multi-agent topologies, between LLM reasoning and deterministic post-passes, between retrieval and direct context loading — and defend the choice with data. - Engineer the context. The hardest part of building a good agent is what goes into the prompt and what comes out. You'll obsess over context windows, tool surfaces, structured outputs, citation grounding, and the prompt itself. - Drive evaluation rigor. Build evals before you build the agent. Diagnose where it fails, fix the root cause, and prove the fix moved the metric. - Use AI tooling like a power user. A meaningful fraction of your day will be spent driving Claude Code, Codex, and similar tools to plan, scaffold, refactor, and debug your own work. We expect you to be faster with these tools than most engineers are without them. - Become a domain expert. Healthcare claims, coding guidelines, and the medical record itself are unavoidable parts of the job. Strong engineers who lean into the domain become outsized contributors here. What We're Looking For Required - 2–4 years of applied ML / AI engineering experience with a Bachelor's in CS, Math, Engineering or equivalent — or a Master's in a similar program with no prior industry experience required. Either way, at least one production-quality system (industry, research, or substantial open-source) you owned end-to-end. - Strong Python engineering. Clean abstractions, type discipline, async, tested code. - Deep, hands-on understanding of agent loops — how a model decides to call a tool, how a tool result re-enters context, how loops terminate, where they fail. - Hands-on experience with at least one major agent SDK — OpenAI Agents SDK, Anthropic SDK / claude-agent-sdk, LangGraph, or equivalent — and an opinion on the tradeoffs. - Working knowledge of how modern coding agents are built and how they engineer context — what goes in the system prompt, how files are read and edited, how long-running tasks are planned and tracked, where they break. - Fluency with Claude Code / Codex as a power user. You should be able to brainstorm, plan, and execute non-trivial engineering tasks with these tools — including reading their source when needed to understand or extend behavior. - Solid command of VS Code and git — branches, rebases, worktrees, conflict resolution, PR workflows. Not optional. - A bias toward measurement: you don't ship without an eval, and you don't believe a number you can't reproduce. Strongly preferred - Experience designing structured outputs (Pydantic / JSON Schema) and tool interfaces that LLMs reliably call correctly. - Familiarity with reasoning models (o-series, Claude extended thinking, Gemini thinking) and a sense of when they earn their cost. - Prior work on long-context, citation-grounded systems where the model must point to evidence, not just answer. - Healthcare, legal, finance, or any other domain where "mostly right" is unacceptable. Nice to have - Document understanding (OCR, layout-aware models, table extraction). - Vision-language models, multimodal retrieval. - Production experience with caching, observability, and cost control on LLM workloads. What We Offer  Work from anywhere in the US! Machinify is digital-first. Top Medical/Dental/Vision offerings FSA/HSA Tuition reimbursement Competitive salary, 401(k) with company match Unlimited PTO Additional health and wellness benefits and perks Flexible and trusting environment where you’ll feel empowered to do your best work  The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $130k-$200k+ based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more.Equal Employment Opportunity at Machinify   We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

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Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans — including many of the top 20 and representing more than 270 million lives — Machinify brings together a fully configurable, content-rich, AI-powered platform along with best-in-class expertise. We're constantly reimagining what's possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. The Role We're building production-grade agentic systems that audit medical claims end-to-end — reading raw medical records, reasoning over coding and clinical guidelines, and producing defensible findings that hold up to clinical and regulatory review. Reaching human-expert accuracy on noisy, long-context documents is one of the hardest unsolved problems in applied AI, and the field is moving weekly. We're hiring an L4 AI Engineer who can step into an ambiguous problem, design an agent system from scratch, and ship it. You won't be plugging into someone else's architecture — you'll be deciding what the architecture should be. What You'll Do - Design agent systems from first principles. Decide the loop, the tools, the context strategy, the evaluation harness. Choose between single-agent and multi-agent topologies, between LLM reasoning and deterministic post-passes, between retrieval and direct context loading — and defend the choice with data. - Engineer the context. The hardest part of building a good agent is what goes into the prompt and what comes out. You'll obsess over context windows, tool surfaces, structured outputs, citation grounding, and the prompt itself. - Drive evaluation rigor. Build evals before you build the agent. Diagnose where it fails, fix the root cause, and prove the fix moved the metric. - Use AI tooling like a power user. A meaningful fraction of your day will be spent driving Claude Code, Codex, and similar tools to plan, scaffold, refactor, and debug your own work. We expect you to be faster with these tools than most engineers are without them. - Become a domain expert. Healthcare claims, coding guidelines, and the medical record itself are unavoidable parts of the job. Strong engineers who lean into the domain become outsized contributors here. What We're Looking For Required - 2–4 years of applied ML / AI engineering experience with a Bachelor's in CS, Math, Engineering or equivalent — or a Master's in a similar program with no prior industry experience required. Either way, at least one production-quality system (industry, research, or substantial open-source) you owned end-to-end. - Strong Python engineering. Clean abstractions, type discipline, async, tested code. - Deep, hands-on understanding of agent loops — how a model decides to call a tool, how a tool result re-enters context, how loops terminate, where they fail. - Hands-on experience with at least one major agent SDK — OpenAI Agents SDK, Anthropic SDK / claude-agent-sdk, LangGraph, or equivalent — and an opinion on the tradeoffs. - Working knowledge of how modern coding agents are built and how they engineer context — what goes in the system prompt, how files are read and edited, how long-running tasks are planned and tracked, where they break. - Fluency with Claude Code / Codex as a power user. You should be able to brainstorm, plan, and execute non-trivial engineering tasks with these tools — including reading their source when needed to understand or extend behavior. - Solid command of VS Code and git — branches, rebases, worktrees, conflict resolution, PR workflows. Not optional. - A bias toward measurement: you don't ship without an eval, and you don't believe a number you can't reproduce. Strongly preferred - Experience designing structured outputs (Pydantic / JSON Schema) and tool interfaces that LLMs reliably call correctly. - Familiarity with reasoning models (o-series, Claude extended thinking, Gemini thinking) and a sense of when they earn their cost. - Prior work on long-context, citation-grounded systems where the model must point to evidence, not just answer. - Healthcare, legal, finance, or any other domain where "mostly right" is unacceptable. Nice to have - Document understanding (OCR, layout-aware models, table extraction). - Vision-language models, multimodal retrieval. - Production experience with caching, observability, and cost control on LLM workloads. What We Offer  Work from anywhere in the US! Machinify is digital-first. Top Medical/Dental/Vision offerings FSA/HSA Tuition reimbursement Competitive salary, 401(k) with company match Unlimited PTO Additional health and wellness benefits and perks Flexible and trusting environment where you’ll feel empowered to do your best work  The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $130k-$200k+ based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more.Equal Employment Opportunity at Machinify   We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!As the Head of Solutions Architecture at Cohere, you will be the strategic leader responsible for leading a global team of Solutions Architects. In this role you will drive sales and revenue growth by designing and delivering cutting-edge AI solutions that meet the needs of enterprise customers worldwide. This role is pivotal in shaping Cohere’s technical narrative, ensuring our solutions align with customer requirements, and directly contributing to the company’s bottom line. In this leadership role you will be both a visionary architect and a results-driven sales leader, bridging the gap between technical innovation and business outcomes.In this role, you will:Drive Revenue Growth: Lead the development and execution of technical sales strategies that directly contribute to revenue targets and market expansion.Scale the Team: Build, mentor, and scale a high-performing global solutions architecture team, ensuring they are equipped to win deals and deliver value to customers.Own the Sales Pipeline: Partner with the sales team to identify, pursue, and close high-value opportunities, serving as the technical expert and trusted advisor to customers.Design Winning Solutions: Architect scalable, secure, and customizable AI solutions that address complex enterprise challenges and differentiate Cohere in the market.Shape Product Development: Collaborate closely with the product team to ensure Cohere’s platform evolves to meet customer needs and drives competitive advantage.Establish Best Practices: Define and implement industry-leading best practices for agentic AI, model customization, and enterprise deployment, ensuring Cohere remains at the forefront of innovation.Optimize Sales Processes: Streamline technical sales processes, from proposal development to customer onboarding, to maximize efficiency and win rates.Key Responsibilities:Architect and deliver end-to-end AI solutions. Design scalable, secure, and customizable NLP and generative AI solutions tailored to complex enterprise workflows.Lead the team and technical engagements with C-suite executives and stakeholders, including workshops, deep dives, and solution presentations.Oversee the deployment and integration of LLMs and custom solutions into production environments, ensuring high performance, security, and scalability.Mentor and guide the solutions architecture team, fostering technical excellence and sales leadership skills.Collaborate with cross-functional teams to ensure seamless alignment between customer needs, product development, and technical execution.Identify and cultivate technical champions within customer organizations to drive adoption and gather actionable feedback.Partner with the sales leadership team to develop and execute global sales strategies, including technical enablement and customer onboarding.Track and report on key sales metrics, including pipeline health, win rates, and revenue contribution.What We’re Looking For:Experience: 10+ years of experience in AI/ML solution architecture, with a proven track record of leading large-scale enterprise projects and teams.Sales Engineering Leadership: 10+ years of experience leading sales engineering teams, with a focus on driving revenue growth and managing global sales efforts.Technical Expertise: Deep knowledge of agentic AI, model customization, and enterprise deployment.Revenue Focus: Demonstrated ability to translate technical solutions into business value and directly contribute to revenue targets.Leadership Skills: Proven ability to build, mentor, and scale high-performing technical teams in a fast-paced, global environment.Strategic Thinking: Strong ability to align technical solutions with business objectives and drive innovation.Communication Skills: Exceptional ability to articulate complex technical concepts to both technical and executive audiences.Enterprise Focus: Experience designing and deploying AI solutions for large enterprises, with a focus on scalability, security, and customization.Global Perspective: Proven experience managing cross-regional teams and adapting strategies to diverse markets.Preferred Qualifications:Background in building and managing scalable AI/ML ecosystems, including multi-cloud deployment strategies.Familiarity with security standards for deploying agent-based AI solutions, including data privacy, model safety, and access controls.Experience working in a startup-like context with a track record of driving rapid growth and innovation.Knowledge of agent orchestration frameworks like Cohere North and experience deploying custom agents to production.Experience with CRM and sales enablement tools (e.g., Salesforce, HubSpot) and technical sales methodologies.Track record of exceeding sales targets and delivering measurable revenue growth.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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About AbridgeAbridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. The RoleOur generative AI-powered products are transforming the practice of medicine—and the inference systems that power them need to be fast, reliable, and world-class. We’re looking for an Engineering Manager to lead and grow our Model Inference team.The Inference team owns the end-to-end technical direction of how our models are served: from architecting low-latency, high-throughput infrastructure to pushing the frontier of LLM serving techniques. You’ll lead a high-performing team of AI inference engineers, partner closely with ML Research and the broader AI Platform, and ensure the systems underpinning every clinician interaction are operating at peak efficiency and reliability.What You’ll DoLead and grow a high-performing team of AI inference engineers focused on building and scaling infrastructure for Abridge’s products and APIsOwn the technical direction of our inference systems—making key decisions around batching, throughput, latency, and GPU utilizationArchitect and scale inference infrastructure for reliability, efficiency, and observability; lead incident responseBenchmark and eliminate bottlenecks throughout the inference stackPartner with ML Research teams on model optimization, quantization, and deploymentDevelop APIs for AI inference used by both internal teams and external customersRecruit, mentor, and develop engineering talent; establish team processes, engineering standards, and operational excellenceWork closely with the GenAI Platform, Data, and Product teams to plan and execute projects that directly impact clinicians and patientsWhat You’ll Bring5+ years of engineering experience with 1+ years in a technical leadership or management roleDeep, hands-on experience with ML systems and inference frameworks (e.g., PyTorch, TensorRT, vLLM, TensorFlow)Strong understanding of LLM architecture (eg. Multi-Head Attention, Multi/Grouped-Query Attention, and common transformer components)Experience with inference optimizations (eg. batching, quantization, kernel fusion, FlashAttention)Familiarity with GPU characteristics, roofline models, and performance analysisExperience deploying reliable, distributed, real-time systems at scaleExperience with parallelism strategies: tensor parallelism, pipeline parallelism, expert parallelismSkilled at hiring and mentorship, with a demonstrated track record of helping engineers grow their skills and careersStrong technical communication and cross-functional collaboration skillsComfortable giving constructive feedback on technical designs and code reviewsHas thrived in a fast-growing startup and knows how to operate with urgency and focusAdded BonusBackground in training infrastructure and RL workloadsSkilled in building secure, compliant systems on major cloud platforms (GCP preferred, AWS experience welcome)Experience with Kubernetes and container orchestration at scalePublished work or contributions to inference optimization researchWhy Work at Abridge?At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. How we take care of Abridgers:Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employeesComprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.Paid Parental Leave: Generous paid parental leave for all full-time employees.Family Forming Benefits: Resources and financial support to help you build your family.401(k) Matching: Contribution matching to help invest in your future.Personal Device Allowance: Tax free funds for personal device usage.Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.Compensation and Equity: Competitive compensation and equity grants for full time employees.... and much more!Equal Opportunity EmployerAbridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.Staying safe - Protect yourself from recruitment fraudWe are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions. 

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About UsAt Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future. What the job involvesAs a Senior Software Engineer on the Platform - Cloud Events team, you will ensure that data captured by Hayden’s devices is properly validated and assessed by the powerful ML models that run in the Cloud. In this role you will level up our ML operations by enabling a more efficient model improvement lifecycle. You will work closely with the Product Team, the Technical Program Managers, and our partner engineering teams that build the edge software and make sense of our sensor data. We’re looking for someone who loves leveling up their team through code review, improving architecture, and thinking systemically. This position is based in San Francisco and it follows a hybrid schedule with at least 3 days in-office per week.  Key ResponsibilitiesBelow are your primary responsibilities. These represent the core areas where you’ll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.Maintain a high level of code quality through code review and documentationOptimize machine learning operations with robust systems and by collaborating across teamsExpand capabilities of event pipeline to satisfy both general and client specific needsReduce cost of doing business with by optimizing usage of cloud resources, especially GPUs Required QualificationsThe qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.Experience: 7+ years of overall experience, 2+ years building high throughput backend servicesCore Skills: Professional experience with Golang and/or Python, distributed systems thinking, ML Ops knowledge a plusPersonal Attributes: Collaborative teammate and code reviewer, detail oriented system designerEducation: BS in Computer Science or related fieldNice to Have: Professional experience with government technology, ML Operations experience, Familiarity with AWS specific implementation of managed services

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At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. This team helps automate audit readiness work while keeping customers in control. This is a rare opportunity to lead a zero-to-one build in one of the fastest-growing areas of our business, transforming Vanta into an AI-first platform.The team's mission is to make AI a core differentiator of Vanta by enabling and accelerating product innovation, and creating reliable, trustworthy, and high-quality customer experiences. The team is currently building out our Vanta Agent product, focused on downmarket and startup customers initially, with plans to scale the product to all customer segments. Core projects include agentic evidence collection, reducing manual work while ensuring the customer remains the final approver in all decisions.In this role, you'll manage a team that's scaling rapidly—currently 7 engineers with plans to grow to scale further throughout the year. You'll work closely with Vanta's AI platform team, product, and GRC subject matter experts to ship AI features that deliver magical customer experiences.Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an Engineering Manager at Vanta:Build and scale a high-performing team, hiring strategically to fill skill gaps as the team growsCoach, mentor, and create an environment where your team can do their best work and deliver for the businessSet direction and guide technical strategy for AI agent and downmarket products, ensuring long-term value aligned with Vanta's business prioritiesPartner closely with product, design, and AI platform teams to ship customer-facing AI features that automate audit work while maintaining human-in-the-loop controlsChampion best practices for applied AI, including prompt engineering, RAG, agentic frameworks, and quality evaluationNavigate rapid change and ambiguity with adaptability, iterating quickly on roadmaps as the team's charter and direction evolveHow to be successful in this role:2+ years of experience managing technical teams of 4-8+ engineersProven track record as a strong individual contributor before transitioning to management, with hands-on applied AI experienceDeep knowledge of building LLM-backed products, including experience with prompting, RAG, agent frameworks, and quality hill-climbingExperience in fast-paced, startup environments; founder background or YC experience is a strong plusStrong adaptability and comfort with ambiguity—you can quickly iterate on roadmaps without too much attachment as priorities evolveExcellent collaboration and influencing skills across engineering, product, design, and cross-functional teamsFamiliarity with Vanta's tech stack (TypeScript, React, Node.js) or willingness to ramp quicklyOpen to using AI to amplify their skills and strengthen their work - demonstrating curiosity, a willingness to learn, and sound judgment in applying AI responsibly to improve efficiency and impact.What you can expect as a Vanta’n:Industry-competitive salary and equityComprehensive medical, dental, and vision coverage, with 100% of employee-only benefit premiums covered for most medical plans16 weeks fully-paid Parental Leave for all new parentsHealth & wellness stipendRemote workspace, internet, and cellphone stipendCommuter benefits for team members who report to the SF and NYC officeFamily planning benefitsMatching 401(k) contribution with immediate vestingFlexible PTO policy, plus 80 hours of Sick Time11 company-paid holidaysVirtual team building activities, lunch and learns, and other company-wide events!Offices in SF, NYC, London, Dublin, Tel Aviv, and SydneyTo provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar-stage growth companies. Final offer amounts are determined by multiple factors and may vary based on candidate location, skills, depth of work experience, and relevant licenses/credentials. #LI-remoteAt Vanta, we are committed to hiring diverse talent of different backgrounds and as such, it is important to us to provide an inclusive work environment for all. We do not discriminate on the basis of race, gender identity, age, religion, sexual orientation, veteran or disability status, or any other protected class. As an equal opportunity employer, we encourage and welcome people of all backgrounds to apply.About VantaWe started in 2018, in the wake of several high-profile data breaches. Online security was only becoming more important, but we knew firsthand how hard it could be for fast-growing companies to invest the time and manpower it takes to build a solid security foundation. Vanta was inspired by a vision to restore trust in internet businesses by enabling companies to improve and prove their security. From our early days automating security monitoring for compliance standards like SOC 2, HIPAA and ISO 27001 to creating the world's leading Trust Management Platform, our vision remains unchanged. Now more than ever, making security continuous—not just a point-in-time check— is essential. Thousands of companies rely on Vanta to build, maintain and demonstrate their trust— all in a way that's real-time and transparent.Referral InstructionsIf you are being referred for the role, please contact that person to apply on your behalf.   

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About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance.We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will:• Build internal apps for enterprise operations across Finance, People, and GTM• Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling• Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries• Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance• Build evals, monitoring, metrics, and regression tests for agentic workflows• Create reusable infrastructure, patterns, and components that other enterprise teams can build on• Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you:• Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs• Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling• Have experience building internal apps, backend services, APIs, workflow systems, or integration platforms• Understand enterprise systems, including controls, approvals, auditability, compliance, and permissions• Have practical AI systems experience with RAG, evals, monitoring, MCP/tool use, structured outputs, or multi-agent workflows• Have strong data architecture fundamentals, including ingestion, modeling, quality, lineage, and governance• Communicate clearly with technical stakeholders, system owners, and business owners• Take high ownership in ambiguous, cross-functional environmentsAbout OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamThe AI Deployment Engineering team partners closely with customers to help them move from experimentation to production with OpenAI’s technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI.The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the RoleWe are looking for an AI Deployment Engineering Manager, Startups to lead and scale the Startups AI Deployment Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical partnerships with OpenAI.This leader will operate in a high-velocity customer segment where founders, CTOs, and technical teams expect speed, judgment, and hands-on problem-solving. They will balance team leadership, technical depth, customer prioritization, and cross-functional influence across Sales, Product, Engineering, Research, and broader go-to-market teams.In this role, you will define how OpenAI supports startup customers at scale: identifying where deep technical engagement can unlock outsized impact, building repeatable deployment mechanisms, and ensuring the team can serve a broad and dynamic customer base without losing quality or strategic focus. In This Role, You WillCraft and continuously refine the strategic vision and operating model for the Startups AI Deployment Engineering team, aligning it with OpenAI’s broader company objectives and the evolving needs of high-growth startup customers.Lead, mentor, and grow a team of high-performing technical ICs supporting startup customers across AI-native, developer-led, and product-led companies.Help startups move from early experimentation to production usage by identifying technical blockers, advising on architecture, and driving practical paths to deployment.Partner closely with Sales to determine where technical engagement can accelerate adoption, production usage, and long-term account growth.Represent the technical voice of startup customers by synthesizing high-signal feedback, especially around developer experience, product gaps, deployment blockers, model performance, and emerging use cases.Translate recurring startup needs into repeatable playbooks, starter packs, reference architectures, internal tooling, and customer-facing assets that help the broader team move faster.Serve as a senior technical escalation point for priority startup customers, including founder-, CTO-, and technical executive-level conversations.Balance urgent customer needs with OpenAI’s broader product and platform priorities, especially when startups request niche features, bespoke support, or accelerated roadmap changes.Coach AI Deployment Engineers on technical quality, customer judgment, prioritization, executive communication, and cross-functional partnership.Partner across Sales, Product, Engineering, Research, and other GTM teams to improve how OpenAI supports startups from early adoption through scaled production usage.You Might Thrive in This Role If YouHave proven experience founding, scaling, or operating within early-stage startups, ideally in technical leadership roles where you owned both product or customer outcomes and technical execution.Have a strong track record of building and leading technical, customer-facing teams in high-growth, ambiguous, or startup-heavy environments.Bring strong technical depth across APIs, platform products, AI/ML systems, developer workflows, and production deployment considerations.Have experience creating scalable operating models, not just managing one-off customer escalations.Are comfortable working directly with founders, CTOs, technical executives, and highly technical ICs.Demonstrate strong judgment about when to go deep for a strategic customer versus when to build repeatable mechanisms for the broader segment.Can translate complex technical and product considerations into clear decisions, practical guidance, and customer-facing recommendations.Operate with speed, iteration, and pragmatic customer impact without sacrificing quality, safety, or OpenAI’s long-term platform strategy.Are personally committed to fostering the safe and beneficial development of AI.Success in This Role May Look LikeIncreased startup account usage, including tokens, requests, and production workloads.A strong cadence of successful customer sprints and production-oriented technical engagements.High-quality customer stories, founder and CTO satisfaction, and referenceable startup wins.Creation of repeatable startup deployment patterns, starter packs, templates, and reference architectures.Strong Product and Research feedback loops informed by startup customer needs and emerging use cases.A healthy, high-performing team with strong prioritization, clear operating mechanisms, and the ability to scale coverage across a high-demand segment.    About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the teamThe AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of OpenAI technologies across developers and enterprises. We act as trusted technical partners, helping customers move from experimentation to production by designing, implementing, and scaling real-world AI applications.The Codex Deployment Engineering team focuses on enabling organizations to adopt next-generation AI coding tools and intelligent automations throughout their software development lifecycle. We partner directly with engineering teams to integrate Codex into their workflows — from early experimentation and pilot design through enterprise-scale production rollout — ensuring AI-enhanced developer experiences are reliable, secure, and deeply embedded within customer environments.About the roleWe are seeking an experienced technical leader to manage a team of AI Deployment Engineers responsible for driving successful Codex adoption across strategic customers. In this role, you will lead engineers who work hands-on with customer development teams to design AI-enabled workflows, deploy production-ready solutions, and establish scalable patterns for AI-powered software development.As a manager, you will define how deployment engagements operate at scale — setting technical strategy, coaching engineers, and ensuring consistent execution across customer implementations. You will serve as both a people leader and technical advisor, partnering closely with Sales, Product, Research, and Engineering teams to translate customer needs into deployment best practices and product insights.Success in this role will be measured by production deployments, sustained developer adoption, and the creation of repeatable deployment patterns that accelerate Codex usage across organizations.This role is open in both our London and Munich office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.In this role, you will:Lead, hire, and mentor a high-performing team of AI Deployment Engineers supporting Codex customers across strategic accounts.Own the operating model and engagement strategy for Codex deployment efforts, ensuring customers successfully move from pilot to production adoption.Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures.Act as the senior technical escalation point for complex customer implementations and deployment challenges.Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities.Help establish repeatable deployment playbooks, technical patterns, and best practices that enable scaled adoption of AI coding tools.Coach engineers to operate as trusted advisors to engineering leadership and executive stakeholders.Synthesize insights from customer deployments and translate them into actionable feedback for internal teams.Champion safe, reliable, and effective adoption of AI-powered development workflows across industries.You might thrive in this role if you:Have 8+ years of experience in technical customer-facing roles such as deployment engineering, solutions architecture, technical consulting, or post-sales engineering.Have 2+ years of experience leading technical teams, including hiring, mentoring, and developing engineers.Have experience deploying Generative AI, developer platforms, or cloud-based software solutions into production environments.Possess hands-on technical experience with software development systems and programming languages such as Python or JavaScript.Understand modern software development lifecycles and how AI tooling transforms developer productivity and workflows.Are an effective communicator who can translate complex technical and business topics to both engineering teams and executive stakeholders.Thrive in ambiguous, fast-moving environments and enjoy building new operating models and teams from first principles.Demonstrate strong ownership, humility, and a commitment to helping both customers and teammates succeed.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the teamThe AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of OpenAI technologies across developers and enterprises. We act as trusted technical partners, helping customers move from experimentation to production by designing, implementing, and scaling real-world AI applications.The Codex Deployment Engineering team focuses on enabling organizations to adopt next-generation AI coding tools and intelligent automations throughout their software development lifecycle. We partner directly with engineering teams to integrate Codex into their workflows — from early experimentation and pilot design through enterprise-scale production rollout — ensuring AI-enhanced developer experiences are reliable, secure, and deeply embedded within customer environments.About the roleWe are seeking an experienced technical leader to manage a team of AI Deployment Engineers responsible for driving successful Codex adoption across strategic customers. In this role, you will lead engineers who work hands-on with customer development teams to design AI-enabled workflows, deploy production-ready solutions, and establish scalable patterns for AI-powered software development.As a manager, you will define how deployment engagements operate at scale — setting technical strategy, coaching engineers, and ensuring consistent execution across customer implementations. You will serve as both a people leader and technical advisor, partnering closely with Sales, Product, Research, and Engineering teams to translate customer needs into deployment best practices and product insights.Success in this role will be measured by production deployments, sustained developer adoption, and the creation of repeatable deployment patterns that accelerate Codex usage across organizations.This role is open in both our London and Munich office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.In this role, you will:Lead, hire, and mentor a high-performing team of AI Deployment Engineers supporting Codex customers across strategic accounts.Own the operating model and engagement strategy for Codex deployment efforts, ensuring customers successfully move from pilot to production adoption.Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures.Act as the senior technical escalation point for complex customer implementations and deployment challenges.Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities.Help establish repeatable deployment playbooks, technical patterns, and best practices that enable scaled adoption of AI coding tools.Coach engineers to operate as trusted advisors to engineering leadership and executive stakeholders.Synthesize insights from customer deployments and translate them into actionable feedback for internal teams.Champion safe, reliable, and effective adoption of AI-powered development workflows across industries.You might thrive in this role if you:Have 8+ years of experience in technical customer-facing roles such as deployment engineering, solutions architecture, technical consulting, or post-sales engineering.Have 2+ years of experience leading technical teams, including hiring, mentoring, and developing engineers.Have experience deploying Generative AI, developer platforms, or cloud-based software solutions into production environments.Possess hands-on technical experience with software development systems and programming languages such as Python or JavaScript.Understand modern software development lifecycles and how AI tooling transforms developer productivity and workflows.Are an effective communicator who can translate complex technical and business topics to both engineering teams and executive stakeholders.Thrive in ambiguous, fast-moving environments and enjoy building new operating models and teams from first principles.Demonstrate strong ownership, humility, and a commitment to helping both customers and teammates succeed.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.If you'd like to build the world's best AI cloud, join us.*Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. The Field Engineering team is a group of ML engineers working hands-on with customers to optimize, deploy, and scale ML workloads on the most advanced GPU infrastructure available. We partner with enterprise, YC, and on-demand customers on some of the most demanding ML use cases in the industry and we're growing.This summer, we're looking for an ML engineering intern to embed with the team, dig into real customer optimization work, and help build the foundation that lets us scale. If you want hands-on experience at the intersection of cutting-edge ML and real-world customer impact, this is the role.What You'll DoLearn directly from ML engineers who made the transition to customer-facing field engineering, gaining firsthand exposure to how deep ML expertise translates into real-world customer impactWork on real, cutting-edge customer workloads running on the most advanced GPU infrastructure available, supporting customer onboarding, optimization engagements, and production deployments across some of the most demanding ML use cases in the industryReview prior optimization work, evaluate strategies against current best practices, and recommend improvementsDevelop a structured optimization playbook and case studies that capture the team's methodology and quantify the value of field engineering work in a repeatable, scalable formatPresent your work to company leadership at the close of the engagementYouCurrently pursuing or just completed a Master's degree in Computer Science, Machine Learning, or a related fieldStrong Python skills with hands-on experience in ML inference, model optimization, benchmarking / evaluations, or applied ML deployment.Have a solid background and general knowledge of machine learning model architectureYou have the skillset to be able to write code (without any AI assistance) to build an ML model and debug from scratch.You understand how models run in production – MLOps tools, open-source models, orchestration strategies.You have a strong understanding of fine-tuning models.Are curious and keep up to date with new models, techniques, strategies, and releases in machine learning and are driven to bring these insights to your work.Can write clearly for both technical and non-technical audiences, translating results is as important as producing themComfortable using Claude or equivalent AI tools as a core part of your daily workflowSelf-directed: given a scoped problem and a mentor, you can break it into milestones and drive it to completionNice to HaveFamiliarity with LLM inference optimization frameworks (vLLM, sgLang, Modular, TensorRT-LLM, or similar)Are able to write tests to create layer-wise benchmarking for ML model performanceFamiliarity with networking, storage, and various orchestration tools / methods.Prior internship at an ML infrastructure, cloud, or GPU hardware companyInterest in or prior exposure to customer-facing engineering, solutions engineering, or developer relationsSalary Range InformationThis is an hourly role, eligible for overtime. The hourly rate for this position has been set based on market data and other factors. However, a hourly rate higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About LambdaFounded in 2012, with 500+ employees, and growing fastOur investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent CoveWe have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOGOur values are publicly available: https://lambda.ai/careersWe offer generous cash & equity compensationHealth, dental, and vision coverage for you and your dependentsWellness and commuter stipends for select roles401k Plan with 2% company match (USA employees)Flexible paid time off plan that we all actually useA Final Note:You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.Equal Opportunity EmployerLambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

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About the role: Come define the future of AI Engineering at the company building the world’s leading agentic data science and analytics platform. As our AI Engineering Lead, you will accelerate the product and company by leveraging frontier AI technology and techniques, collaborating closely with product and engineering, and building and developing a world-class team of AI Engineers. What you will do: Stay up-to-date on the latest in AI technology and work with engineering teams to push the frontier of product capabilities Define and implement the future of the AI Engineering function at Hex as we scale Hire and mentor an exceptional team of AI Engineers Support an exceptional developer and research experience for teams working with AI technology Deliver high-performing shared AI infrastructure, including search systems About You: You have 4+ years of people management experience and leading high-performing teams You have deep familiarity with modern AI technology as well as classical ML systems and a passion for sharing that with others. Technologies of particular interest include LLMs and transformer models, agentic workflows, context management, and agentic evals. You are obsessed with driving business outcomes and delivering value to customers You are rigorous but pragmatic, balancing good experimental design with early-stage agility You are a strong communicator and love collaborating with other roles and teams to drive outcomes You are a talent magnet, with the ability to attract and retain exceptional AI talent Our stack Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack. This is a full-time role based out of either our San Francisco or New York office. Employees are encouraged to come into the office at least twice a week, with Tuesdays and Thursdays being our main in-person days. In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off. The salary range for this role is: $246,000 - $329,000 The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the interview process. By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy. Hex Technologies uses AI-assisted tools as part of our application review process, including for resume screening and fraud detection. These tools help our team evaluate applications and verify applicant information. All AI-generated recommendations are reviewed by a member of our recruiting team before any hiring decision is made. No application is automatically rejected based solely on an AI tool's output.

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ABOUT POOLSIDEIn this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.Poolside exists to be this company: to build a world where AI will be the engine behind economically valuable work and scientific progress. We believe the fastest way to reach AGI lies in accelerating software development itself, by reshaping the developer experience with agentic systems, coding assistants, and the frontier models that power them. We deploy these systems directly into the development environments of security-conscious enterprises.ABOUT OUR TEAMWe were founded in the US and have our home there, but our team is distributed across Europe and North America. We get our fix of in-person collaboration (and croissants) in Paris each month for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year.Our team is a multidisciplinary blend of research, engineering, and business experts. What unites us is our deep care for what we build together. We’re in a race that requires hard work, intellectual curiosity, and obsession; to balance this intensity, we’ve assembled a team of low ego and kind-hearted individuals who have built the special culture Poolside has. By building collaboratively and with intention, we create a compounding effect that moves the entire company forward towards our mission: reaching AGI through intelligence systems built for software development.ABOUT THE ROLEYou’ll be working on our data team focused on the quality of the datasets being delivered for training our models. This is a hands-on role where your #1 mission would be to improve the quality of the pretraining datasets by leveraging your previous experience, intuition and training experiments. This includes synthetic data generation and data mix optimization. You’ll closely collaborate with other teams like Pretraining, Postraining, Evals, and Product to define high-quality data needs that map to missing model capabilities and downstream use cases.Staying in sync with the latest research in the fields of dataset design and pretraining is key to success in this role. You will constantly lead original research initiatives through short, time-bounded experiments while deploying highly technical engineering solutions into production. With the volumes of data to process being massive, you'll have a performant distributed data pipeline together with a large GPU cluster at your disposal.Curious about the tech? Take a deep dive into our pretraining data stack in this blogpost from our 'Model Factory' series.YOUR MISSIONTo deliver large, high-quality, and diverse datasets of natural language and source code for training Poolside models and coding agents.RESPONSIBILITIESFollow the latest research related to LLMs and data quality in particular. Be familiar with the most relevant open-source datasets and models.Design and implement complex pipelines that can generate large amounts of data while maintaining high diversity and optimizing the resources available.Closely work with other teams such as Pretraining, Posttraining, Evals and Product to ensure short feedback loops on the quality of the models delivered.Suggest, conduct and analyze data ablations or training experiments that aim to improve the quality of the datasets generated via quantitative insights.SKILLS & EXPERIENCEStrong machine learning and engineering backgroundExperience with Large Language Models (LLM), including:Understanding of transformer architectures and how LLMs learnData ablations and scaling lawsMid-training and Post-training techniquesTraining reasoning and agentic modelsExperience with evals tracking model capabilities (general knowledge, reasoning, math, coding, long-context, etc)Experience in building trillion-scale pretraining datasets, and familiarity with concepts like data curation, deduplication, data mixing, tokenization, curriculum, impact of data repetition, etc.Excellent programming skills in PythonStrong prompt engineering skillsExperience working with large-scale GPU clusters and distributed data pipelinesStrong obsession with data qualityResearch experience:Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc. - is a nice to haveCan freely discuss the latest papers and descend to fine detailsIs reasonably opinionatedPROCESSIntro call with one of our Founding EngineersTechnical Interview(s) with one of our Members of EngineeringTeam fit call with the People teamFinal interview with one of our Founding EngineersBENEFITSFully remote work & flexible hours37 days/year of vacation & holidaysHealth insurance allowance for you & dependentsCompany-provided equipmentWell-being, always-be-learning & home office allowancesFrequent team get togethersDiverse & inclusive people-first culture

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Forward Deployed Engineer Aussie Engineer looking to make the move to the US? Join us and build the AI platform that's rewriting a $50B industrySalary range - $180-220k USD + Equity + Benefits + Relocation Assistance + US Sponsorship  About HaastWe're building one of the first agentic systems for enterprise legal and compliance teams that actually automates their manual work. End-to-end. Delivering 80% faster compliance reviews and 4x productivity gains.We recently closed a $12M USD Series A (Peak XV Partners, DST Global, Airtree) and are growing fast in the US; building the infrastructure that will completely re-define how enterprises think about compliance.Think Canva for design. Atlassian for projects. Haast for compliance. The ProblemCompliance is a $50B global challenge. Enterprise legal and compliance teams spend a significant amount of time manually reviewing documents against policy, spotting regulatory risk, and signing off on content before go-to-market. It's painful and it's mission-critical.We're building the infrastructure that makes this manageable at scale. You'll be working on systems that directly reduce risk and unlock productivity for some of the world's largest organisations. The RoleAs our first US based Engineer; you'll be the technical bridge between our product vision and our customers' reality. You're a full-stack engineer who thrives at the intersection of innovation and execution, building our platform while staying connected to the teams actually using it.You'll split your time between heads-down building (shipping code that matters) and being engaged with customers, understanding their pain points firsthand, iterating on features in real-time, and using that feedback to shape our product direction. You'll own end-to-end technical decisions: designing systems, shipping to production, and iterating based on direct customer interaction.This is high-autonomy work. You'll collaborate directly with our founding team, move at startup velocity, and have genuine influence over both our architecture and product roadmap.  What You'll OwnDesign, architect, and ship full-stack features that directly solve our customers compliance challengesOwn the technical relationship with key customers; implementing solutions, gathering requirements, and translating feedback into product improvementsBuild scalable services and APIs that power our LLM compliance platform while keeping the customer experience front and centerMake high-impact technical decisions quickly, knowing that you'll be accountable to both our engineering standards and our customersChallenge assumptions on "why" and "how", you'll directly influence what we build and how we build itShape our product roadmap and engineering practices as we scale from Series A to market leadership Who We're Looking ForYou've built full-stack systems at meaningful scale; you're equally comfortable architecting backend services and shipping frontend code that customers interact with dailyYou're deep on one or more of: Go, Node.js/TypeScript, or Python, and you're fluent enough across the stack to own features end-to-endYou understand APIs, distributed systems, and the tradeoffs between speed and reliability in production environmentsYou genuinely enjoy working with customers; you're not just shipping features, you want to understand the human problem you're solvingYou've shipped in fast-moving environments and understand what it takes to move quickly without breaking thingsYou're curious about how LLMs work and excited about building practical applications on top of them, not just the theory Why Join HaastCompetitive benefits: PTO, Health, Dental, Vision, 401k Real impact, day one: Your code runs inside the workflows of major global enterprises immediately. You're solving mission-critical compliance problems that directly reduce risk and unlock productivity. Forward-deployed influence: You'll spend time with customers, understanding their pain points and having direct input into product decisions. Your customer insights will shape our roadmap.Equity upside: We're building a generational company in a $50B market. You'll own a meaningful stake in that value creation and be part of the defines how Haast scales. We believe in sharing success with the people who build it.Exceptional learning velocity: You'll learn more about scaling systems, working with customers, building products, and navigating the demands of a fast-growing startup in 12 months here than most roles offer in three years.Engineering-driven culture: No red tape. We hire smart people and get out of their way. Your voice matters in how we build.Flexibility and community: Fully remote across the US or Canada.   How to ApplyWe're looking for people who've shipped things they're proud of and want to work on a problem that genuinely matters.Apply with:Your CVA brief note on this question: Tell us about a time you worked with customers to ship something they actually needed. What did it take to achieve the outcome? No closing date. We review applications on a rolling basis. At Haast, we believe bold ideas come from diverse perspectives. We're committed to building a team that reflects the world we work in. Even if you don't tick every box, we'd love to hear from you. #LI-Remote

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Toloka AI supports frontier model post-training by building domain-specific reinforcement learning environments, tasks, and evaluation frameworks designed by real practitioners. Mindrift, powered by Toloka — a leading enterprise AI and machine learning data partner since 2014 — connects top domain experts with cutting-edge AI initiatives. Backed by Toloka’s deep expertise in scalable data generation, crowd technology, and applied ML systems, Mindrift enables experts to shape how next-generation generative models learn, reason, and perform.We are launching a Management Consulting domain focused on translating real-world consulting engagements into structured learning environments for advanced AI systems. To do this credibly, we are assembling a team of strategy consultants from top-tier firms who can convert authentic project experience into end-to-end examples — from problem structuring and work planning to analysis, synthesis, and client-ready recommendations.You will join a growing team of consultants from leading strategy firms shaping how AI learns high-level business reasoning.Important: This role is exclusively for consultants with direct experience at a top-tier strategy consulting firm. If you do not have hands-on project experience at one of the firms listed below, please do not apply. This requirement ensures the domain is built by practitioners trained to the highest standards of structured problem-solving and client delivery.Eligible firms: McKinsey & Company, Boston Consulting Group (BCG), Bain & Company, Oliver Wyman, Roland Berger, Monitor Deloitte (Deloitte S&C), EY-Parthenon, Kearney, and Strategy& (PwC).Who We’re Looking ForConsultants with 3+ years of experience at one of the firms listed above, with hands-on project experience in:Structuring ambiguous client problems into workable analytical plansBuilding financial models, market analyses, or synthesized findings from messy inputsProducing client-ready deliverables under time pressureForming and defending recommendations under uncertaintyNo deep technical background is required — we will onboard you on the lightweight tools involved.What You’ll DoBuild realistic consulting project environments — create detailed project scenarios grounded in real engagement dynamics: industry context, financials, constraints, conflicting inputs, and incomplete information.Design structured consulting tasks for AI agents — break projects into discrete tasks that mirror real consulting work: market sizing, commercial due diligence, cost optimization, growth strategy, operational diagnosis, benchmarking, and more.Define evaluation criteria and quality standards — develop grading frameworks, evaluation rubrics, and golden-answer solutions for each task, used to train and calibrate an LLM-based grading system that evaluates AI outputs at scale.This is a remote, project-based, individual-contributor role focused on analytical design and evaluation.Skills & Requirements3+ years at McKinsey, BCG, Bain, Oliver Wyman, Roland Berger, Monitor Deloitte, EY-Parthenon, Kearney, or Strategy&Strong structured problem-solving and hypothesis-driven thinkingAbility to translate vague problems into clear analytical steps and deliverablesHigh attention to logical consistency and output qualityIndependent, self-directed working styleClear written English (B2+)CompensationOn this project, contributors can earn up to $60 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.