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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.About the TeamThe ML Infrastructure team builds the systems that power every stage of Decagon's model lifecycle. We own the platforms for model training, the infrastructure for model evaluation and experimentation, and the routing layer that manages inference across multiple providers.We work at the intersection of research and production: translating cutting-edge ML techniques into reliable, scalable systems that run in customer environments. We collaborate closely with Research, Infrastructure, and Product teams to ensure models train efficiently, serve reliably, and deliver exceptional user experiences.The team values technical rigor, pragmatic decision-making, and building systems that others love to use. About the RoleWe're hiring a Staff ML Infrastructure Engineer to own the platforms powering Decagon's model training and inference. You'll build distributed training systems, design inference architecture across multiple providers, and create the frameworks that let our Research and Product teams ship faster.This role is for someone who thrives on technical depth, can lead multi-quarter initiatives, and wants to shape the long-term architecture of our ML stack. In this role, you willDesign and build distributed training platforms for LLM and multimodal fine-tuning and post-training at scaleImplement and integrate state-of-the-art training algorithms into production pipelinesOwn inference architecture and multi-provider routing, including failover and optimizationResearch and implement inference optimizations including quantization, speculative decoding, and batching strategiesLead initiatives to improve latency and cost efficiency across the training and serving stackBuild evaluation and experimentation infrastructure that enables rapid, reliable iterationDrive technical direction, mentor engineers, and establish best practices for ML infrastructure Your background looks something like this8+ years building ML infrastructure or production systems at scaleDeep experience with distributed training: multi-node GPU clusters, fault tolerance, and optimizationStrong understanding of LLM inference: latency optimization, provider tradeoffs, and serving architectureProficiency in Python and modern ML frameworks (PyTorch, JAX, or TensorFlow)Proven track record leading complex, multi-quarter technical projects BenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your best Compensation$300K – $430K + Offers Equity

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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About Snorkel We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end. Main Responsibilities Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform. Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows. Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role. Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow. Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup. Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices. Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI. Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams. Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI. Annual travel up to 25%. Preferred Qualifications B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience. 3+ years of customer-facing experience in the design and implementation of AI/ML solutions. Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow). Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI). Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement. Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos. Ability to work in a fast-paced environment and balance priorities across multiple projects at once. Compensation range for Tier 1 locations of San Francisco Bay Area $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Locations Redwood City, CA - Hybrid; San Francisco, CA - Hybrid - US #LI-CG1Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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About the team The Safety Systems org ensures that OpenAI’s most capable models can be responsibly developed and deployed. We build evaluations, safeguards, and safety frameworks that help our models behave as intended in real-world settings.The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework.Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.The mission of the Preparedness team is to:Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards risks whose impact could be catastrophicEnsure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systemsPreparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society.About the roleThis role leads the Automated Red Teaming (ART) effort: building scalable, research-driven systems that continuously discover failure modes in our models and mitigations — and translate those findings into actionable, production-facing improvements. The goal is to maximize counterfactual reduction in expected harm by finding the highest-leverage, least-covered weaknesses early and reliably.In this role you willYou will own the research and technical direction for automated red teaming across catastrophic risk areas, with an initial emphasis on:Automated classifier jailbreak discovery (cyber and bio)Automated bio threat-development elicitation (worst-feasible planning uplift)CoT monitoring evasion probing (and adjacent loss-of-control evaluations)You will partner tightly with:Vertical risk teams (Cyber, Bio, Loss of Control) to define threat models, prioritize targets, and land mitigationsThe Classifiers team to turn discovered attacks into training data, evals, and measurable robustness gainsProduct / eng / safety stakeholders to ensure ART outputs are operationally useful (not just interesting)You might thrive in this role if you:Feel a strong pull toward AI safety, and you’re motivated by reducing real-world catastrophic risk (not just publishing cool results).Love breaking systems (responsibly) — you get energy from finding weird, high-severity failure modes and turning them into concrete fixes.Have strong applied research instincts, especially around evaluations: you’re good at designing experiments that are reproducible, interpretable, and hard to fool.Bring hands-on experience with LLMs and agents, including multi-turn behaviors, tool use, and the ways models adapt to constraints.Are comfortable building scalable automation, not just prototypes — you can turn red-teaming ideas into pipelines that run continuously and produce high-signal outputs.Have solid software engineering fundamentals (data structures, algorithms, testing discipline) and you can work effectively in a production-adjacent environment.Think in threat models and incentives, and you naturally ask “what would an attacker do next?” or “how would this fail under pressure?”Can translate messy findings into action, communicating clearly with researchers, engineers, product, and policy — and driving alignment on what to fix first.Care about efficiency and prioritization, and you’re happy to say “no” to low-leverage work to focus on what moves the risk needle.(Nice to have) Experience in adversarial ML, security research / red teaming, abuse prevention systems, or large-scale eval infrastructure.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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Join the Sleep Fitness MovementAt Eight Sleep, we’re on a mission to fuel human potential through optimal sleep. As the world’s first sleep fitness company, we’re redefining what it means to be well-rested and building the most advanced hardware, software, and AI technology to make it possible. Our products power peak mental, physical, and emotional performance by transforming every night of sleep into a personalized, data-driven recovery experience. We are trusted by high performers, professional athletes, and health-conscious consumers in over 30 countries worldwide. Recognized as one of Fast Company's Most Innovative Companies in 2019, 2022, and 2023, and twice named to TIME's “Best Inventions of the Year.” We operate like a high-performance team: fast, focused, and motivated by impact. We don’t just ship; we iterate, refine, and obsess over the details that help our members sleep better and wake up stronger. Every role at Eight Sleep is a chance to create cutting-edge technology, collaborate with world-class talent, and help shape a future where sleep isn’t passive - it’s a powerful tool for living better. If you’re tired of the ordinary and driven to build at the edge of what’s possible, this is your moment. Join us and lead the movement that’s transforming how the world sleeps and what we’re all capable of when we wake up.High Standards. No Apologies.We operate with intensity because our mission demands it. At Eight Sleep, we bring the same mindset as the world’s top performers: focused, relentless, and always pushing to be in the top 1% of our craft. Think Kobe Bryant’s mamba mentality, applied to bold ideas, next-gen tech, and flawless execution. This isn’t a 9-to-5. Our team is deeply committed, often putting in 60+ hours a week –not because we’re told to, but because we’re invested. We’re here to build fast, push limits, and deliver without compromise. If you thrive under pressure and want to do the most meaningful work of your career, you’ll feel right at home. If you’re looking for something easier –this isn’t it.The RoleEight Sleep is the first sleep fitness company. At Eight Sleep we design products at the forefront of sleep innovation. Our mission is to make people’s sleep count for more, using innovative technology, minimalistic design, and proven clinical science to personalize and improve each night for everybody—changing the way people sleep forever and for better.Our temperature-regulated technology, the Pod, is an absolute game changer. It improves people's health and happiness by changing the way they sleep. The Pod was recognized two years in a row by TIME's “Best Inventions of the Year.” It is available for purchase in North America and internationally. Backed by leading Silicon Valley investors including Valor Equity Partners, Founders Fund, Khosla Ventures and Y Combinator, we’ve raised over $150 million (Series C) to date. We were recognized as one of Fast Company’s Most Innovative Companies in Consumer Electronics in 2019, 2022, and 2023.That is why Eight Sleep is looking for research scientists with a passion for using AI & Machine Learning to transform sensor data into personalized intelligent health & fitness experiences. Today, we offer heart rate, heart rate variability, sleep, and other metrics. Tomorrow, your imagination will unlock new meaningful metrics that will induce behavior change for better sleep and better health. To do so, you will work closely with a cross-functional R&D and production team to prototype and to ship solutions.We are seeking someone who is passionate about health technologies and about making an impact on health outcomes. We look for people who tackle problems with a system approach, and make data driven decisions to deliver the best products to our users.How you'll contributeExample projects include:Autopilot Thermoregulation: Advance the Pod’s adaptive thermoregulation system - the “autopilot” system that continuously learns and reacts to micro-events like restlessness or awakenings. Design policies that optimize comfort and sleep quality in real time through reinforcement learning and closed-loop control.Health Foundation Modeling: Develop a multimodal health foundation model that integrates physiology and environmental context - learning from Pod signals, wearable sensors, and contextual data - powered by one billion+ hours of sleep data at Eight Sleep.Behavioral simulations: Build a high-fidelity physiological simulator that models how daily behaviors ripple into tonight’s sleep and tomorrow’s readiness. This initiative aims to create a non-invasive, always-on model of healthy aging powered by Pod biosignals and continuous physiological data. What you'll need to succeedExpertise in at least one area of machine learning and artificial intelligence (e.g., self-supervised learning, multi-modal ML, model optimization, NLP, LLM)Strong interest in applying machine learning to health related problems and dataExperience using a programming language (Python, C/C++ etc.) to manipulate data, draw insights from large data sets, and train machine learning models3+ years of practical experience applying ML to solve real-world problems or relevant quantitative and qualitative research and analytics experiencePhD in Computer Science, Machine Learning, AI, Statistics, Mathematics, or related quantitative field with a notable publication record; or BS/MS with publications at top venues (e.g. NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ACL, EMNLP, INTERSPEECH) Why join Eight Sleep?Innovation in a culture of excellenceJoin us in a workplace where innovation isn’t just encouraged - it’s a standard. Our flagship product, the Pod, is a testament to our culture of excellence, beloved by hundreds of thousands of customers worldwide. At Eight Sleep, you will be part of a team that continuously pushes the boundaries of technology in sleep fitness.Immediate responsibility and accelerated career growthFrom your first day, you’ll take on substantial responsibilities that have a direct impact on our core business and product success. We are a small team that empowers you to own your projects and see the tangible effects of your efforts, enhancing both your professional growth and our company’s trajectory. Your path will be challenging but rewarding, perfect for those who thrive in fast-paced environments aiming for high standards.Collaboration with exceptional talentWork alongside other bright minds like you: at Eight Sleep exceptional intelligence and a passion for breakthroughs are the norms. Our team members are not only experts in their fields but also avid innovators who thrive in our dynamic, fast-paced environment.Equitable compensation and continuous equity investmentWe extend equity participation to every full-time team member, recognizing and rewarding your direct contributions to our success. This includes periodic equity refreshments based on performance, ensuring that as Eight Sleep grows and succeeds, so do you – perfectly aligning your achievements with the broader triumphs of the company. Pay grows rapidly as you accumulate experience with Eight Sleep and translate it into concrete impact.Your own Pod - and other great benefitsEvery Eight Sleep employee receives the very product that defines our mission: a Pod of their own. If you join us you’ll get your own Pod, along with other benefitsAt Eight Sleep we continually celebrate the diverse community different individuals cultivate. As an equal opportunity employer, we stay true to our values by ensuring everyone feels they can flourish and grow. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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Join blp – The #1 Solution for ERP Automationblp is a high-performance ETH and HSG spin-off redefining ERP automation with AI. We solve real enterprise problems with cutting-edge tech and a strong sense of ownership. Our solution is in production across 40+ countries, used by 20'000+ daily active users, automating 70'000+ processes every day.Our AI-driven ERP automation is transforming finance, procurement, logistics, sales, and more. As one of Switzerland's fastest-growing SaaS scale-ups, we are proudly self-financed and fully employee-owned.Our success stems from deep expertise in technology and business processes, delivering a superior product with an outstanding product-to-market fit, proven by our growing customer base, including Fortune 500 companies.Our rapid growth and career opportunities have been recognised with the LinkedIn Top Startup Award, and we’re just getting started. Our HQ? Zürich’s iconic Bahnhofstrasse, a fitting home for a company redefining how businesses operate.Ready to build the future? Join blp today.About the positionWe're giving you the keys to the machine. As our Applied AI Engineer, you'll have a founder-level mandate to build and ship AI-powered internal tools that make our hiring, finance and ops workflows 10x faster — not 10% faster. You'll work at the frontier of what's possible with LLMs, AI agents, and emerging AI tooling, and apply it where it matters most: inside our own company. Key ResponsibilitiesBuild and ship AI-powered internal tools fast — we're talking days and weeks, not quartersEvaluate, integrate, and chain the latest AI models, APIs, and frameworks (LLMs, agent frameworks, embedding pipelines, AI coding tools) into production-ready internal solutionsCreate compounding leverage — every tool you build should free up hours across the entire companyWrite clean, maintainable code that integrates with our existing systems — APIs, databases, third-party services — and doesn't break at scaleOwn your deployments end-to-end: build it, test it, ship it, monitor it — and build it well enough that it runs reliably without babysittingRequirementsTechnical background with real building experience — CS degree, bootcamp, self-taught, we don't care as long as you've shipped things that workYou've built with modern AI tooling (LLMs, AI coding assistants, workflow automation) and you're obsessed with what's coming nextStartup or entrepreneurial DNA — you've either founded something, built an internal tool that became critical infra, or hacked together solutions that people actually usedYou move fast, communicate clearly, and love collaborating with non-technical teams to understand their pain points and turn them into elegant, automated solutionsFluency in English, German is a plusBonus: experience with tools like Make, n8n, Retool, Supabase, or similar — but honestly, we care more about your ability to learn any tool in a weekendBenefitsSolve real problems, fast. Join a high-growth deep-tech startup tackling real-world challenges for global industry leaders.Build from zero to one. Take ownership of our internal tooling landscape — shaping its foundations and direction from the ground up.Opportunities to grow. You're controlling your personal development and career trajectory in a rapidly growing, internationally expanding startupExceptional colleagues. You'll be growing alongside individuals from exceptional academic backgrounds and careers

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About the teamOpenAI’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and durable products.The FDE Platform team is primarily a leverage function that scales the FDE org’s impact to OpenAI’s platform and products. We provide hands-on leverage by embedding with customer-tagged FDE pods to aid in architecting, product shaping, refactoring, and building. This team is perfect for highly collaborative software engineers who love innovating on cutting-edge products with other builders.About the rolePlatform Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments.You will partner with customer-tagged FDEs who are driving delivery and customer outcomes, and embed where you can provide the highest leverage. In practice that means working in the trenches on architecture, product shaping, refactoring, hardening, and reusable abstractions, while preserving the pod’s ownership of customer understanding and day-to-day execution. You will also collaborate closely with our B2B Platform Team and other long-term owners to align early on what should generalize, what should remain customer-specific, and what “ready for handoff” looks like.This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically <10%, with occasional spikes for key embeds or launches.In this role you willProvide hands-on leverage to customer pods: embed with customer-tagged FDE teams to support generalization, contributing directly in architecture, product shaping, refactoring, and implementation.Turn repeated signals into platform bets: translate cross-customer patterns into crisp hypotheses with clear success criteria, scope, and a validation plan that fits real account constraints.Raise the engineering bar through tooling and mentorship: set org-wide quality norms through high-signal code review and pairing, and build lightweight developer tooling that makes good architecture, readability, and correctness the default across FDE.Collaborate as part of cross-functional platform teams: partner closely with B2B Product, customer-tagged FDEs, ops, and business partners to bring the right products and platform capabilities to market.Lead complex platform capabilities end-to-end when needed: for high-leverage primitives like our Context Platform, act as DRI from requirements through implementation, make key tradeoffs explicit, and pull in customer pods early to keep the work grounded in real deployments.You might thrive in this role if youBring 5+ years of software engineering or ML engineering experience with a track record of shipping 0→1 capabilities that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus.Have owned customer-adjacent technical work end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time).Have built or operated systems where reliability, security, and governance materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening).Communicate clearly across engineering, product, go-to-market, and executive audiences, simplifying complex ideas and translating technical tradeoffs into adoption impact, sequencing decisions, and measurable outcomes. You can credibly “pitch” a platform bet in a customer conversation.Default to systems thinking: you turn ambiguous feedback, failures, and escalations into durable product requirements and reusable platform capabilities, not one-off fixes or bespoke delivery work.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 Prospera AIWe’re building Sophie, a multi-agent AI orchestrator that helps wealth management advisors deliver more personalized, effective service to their clients.Our platform analyzes behavioral patterns, communication preferences, and emotional states to transform how advisors understand and serve their clients.We’re a small, well-funded team at an exciting inflection point—our technology works, customers love the product, and now we’re building the engineering team to scale. The RoleWe’re looking for an AI/Backend Engineer to own and evolve our LLM orchestration pipeline. You’ll be the first dedicated engineering hire, working directly with our CTO to transform Sophie from a working prototype into a scalable, enterprise-ready platform.This is a high-impact, high-autonomy role. You’ll shape technical decisions that define the product for years to come.What You’ll DoOwn the AI PipelineDesign and optimize our multi-agent orchestration systemImplement parallelization and streaming to dramatically reduce response latencyBuild robust prompt management with versioning and A/B testing capabilitiesBuild RAG SystemsDesign retrieval-augmented generation for accurate, contextual responsesWork with vector databases, embeddings, and relevance scoringOptimize for both speed and accuracy at scaleDevelop Production APIsBuild developer-friendly APIs connecting our AI capabilities to the frontendDesign for future integrations with CRMs and advisor toolsImplement proper authentication, rate limiting, and documentationShape the FoundationEstablish code review practices and testing standardsDocument architecture decisions for future team membersContribute to technical patents and IP developmentWhat We’re Looking ForMust Have4+ years production Python experience (async patterns, type hints)Hands-on experience with LLM APIs (OpenAI, Anthropic, or similar)Strong understanding of prompt engineering and multi-step LLM workflowsProduction API development experience (FastAPI or similar)Strong SQL and PostgreSQL skillsGreat to HaveExperience with RAG systems and vector databases (Pinecone, Weaviate, pgvector)Streaming/real-time implementation experience (SSE, WebSockets)TypeScript/JavaScript familiarityFinTech or regulated industry backgroundHow You WorkStrong UX intuition—you notice when flows have one too many clicksPragmatic perfectionism—you know when to polish and when to shipClear communicator who can explain technical constraints in business termsCollaborative mindset—frontend doesn’t exist in isolationHow You WorkSelf-directed and comfortable with ambiguityStrong written communication (async-first culture)Pragmatic problem-solver who ships iterativelyCollaborative mindset with ego-free approach to feedbackWhat This Role Is NotWe want to be upfront about expectations:Not a pure ML/research role—you’ll apply LLMs, not train themNot a management role—near-term focus is individual contributionNot fully autonomous—you’ll collaborate closely with the CTO on architectureNot 9-to-5—startup intensity applies, though we respect work-life balanceCompensation & BenefitsEquity: Meaningful early-stage grant with 4-year vestingEquipment: Professional Laptop ready to work with AI provided + stipend for remote work when 6 month mark is metTime Off: Flexible PTO with a minimum 15 days encouragedLearning: $1,000 annual professional development budgetSchedule: Flexible hours with 3-4 hours daily overlap (Americas timezones)

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Exa is building a search engine from scratch to serve every AI application. We build massive-scale infrastructure to crawl the web, train state-of-the-art embedding models to index it, and develop super high performant vector databases in Rust to search over it. We also own a $5M H200 GPU cluster that regularly lights up tens of thousands of machines.Our Infrastructure Team builds the underlying tooling and infrastructure that powers all Exa's systems. Basically, we need more infra engineers to build the machine that builds the machine so that we can move as fast as possible as an engineering org. That could mean building GPU cluster orchestration in Kubernetes, map-reduce batchjobs on Ray, or the best observability tooling in the world. Desired ExperienceYou have experience designing and operating large-scale infrastructure - GPU clusters or large Kubernetes clusters or cloud batchjob systemsYou bring an obsessive mindset — always thinking about reliability, observability, and optimization across the entire stack.Example ProjectsBuild the Kubernetes orchestration on a $20M GPU clusterScale our AWS batchjob system to handle map reduce jobs over 10s of thousands of machinesDesign GPU scheduling software so we max out our cluster utilizationBuild observability into our production systemsThis is an in-person opportunity in Singapore. We’re happy to sponsor international candidates.

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About ClarionAt Clarion, we’re rebuilding how healthcare communicates in the age of AI.Today, clinics miss 30–40% of patient calls, while staff are overwhelmed by administrative work. We believe AI agents should handle these workflows—scheduling, billing, prescription refills, and follow-ups—so healthcare teams can focus on actual patient care.We’re building the communication infrastructure modern healthcare needs. Our AI agents don’t just answer calls—they complete workflows end-to-end, ensuring patients never go unheard. To date, we’ve handled hundreds of thousands of patient interactions across virtual care companies, health systems, and a $5B health insurance company.Clarion was founded by a Stanford/Harvard-trained physician (founding team at Two Chairs and Ophelia) and an ex-Amazon Alexa engineer who led AI/ML teams at Salesforce. We’ve raised $5.4M from Accel, Y Combinator, Sequoia (Scout), and leading healthcare founders. We’re an in-person team in New York, moving fast to solve one of healthcare’s most critical problems.Why This Role Is SpecialReal traction, early-stage impact: Dozens of paying customers, rapidly growing revenue, and the chance to shape core systems at an inflection point.Mission-critical problem: Healthcare communication failures affect millions daily—your work directly improves patient access and outcomes.Elite technical context: Work closely with founders who deeply understand both healthcare operations and advanced AI systems, enabling fast decisions and real ownership.What You’ll OwnLead the deployment, performance, and reliability of AI agents operating in live, high-stakes healthcare environments.Architect and scale full-stack systems integrating with EHRs, legacy healthcare platforms, and real-time voice infrastructure.Drive technical strategy for customer-facing solutions, collaborating with product and engineering to translate client needs into scalable architecture.Mentor engineers and set standards for code quality, testing, security, and HIPAA-compliant development.Shape product roadmap by identifying systemic challenges in customer workflows and proposing high-leverage technical solutions.Interesting Technical ChallengesGenerative AI at Scale: Design and operate production systems using LLMs with rigorous safety, alignment, and real-time monitoring at enterprise scale.Real-time voice infrastructure: Build ultra-low-latency systems supporting thousands of concurrent calls with 99.99% uptime.Fragmented healthcare systems: Design resilient abstraction layers across modern APIs and legacy platforms while maintaining security and compliance.Highly Personalized Experiences: Develop adaptive AI that retains patient context across sessions, personalizes tone and flow, and delivers conversations indistinguishable from human care.What We’re Looking For5+ years of experience designing, building, and scaling production systems in high-reliability environments.Strong full-stack expertise with Node.js, TypeScript, React, and PostgreSQL, plus solid system design instincts.High ownership and agency—you thrive in ambiguity and take responsibility for outcomes.Proven ability to mentor engineers, lead cross-functional efforts, and communicate technical trade-offs clearly.You’ll be a great fit if you enjoy owning complex systems end-to-end, solving hard problems under real-world constraints, and working closely with customers and teammates to deliver mission-critical software.Interview ProcessWe move quickly and communicate clearly at every stage:Intro Chat (30 min, Virtual): Background, role context, and leadership philosophy.Technical Deep Dive (1 hr, Virtual): System design and architecture with the CTO and a senior engineer.Onsite Team Day (Half Day, NYC): Collaborate on real problems, present a past project, meet the team, and assess mutual fit.Decisions are typically made within 24 hours of each stage.

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About ClarionThe hardest part of healthcare shouldn’t be getting an appointment. Today, medical staff drown in backlogs of calls, faxes, and scheduling requests. Patients struggle to get the right care at the right time, staff members burn out, and clinics lose billions in revenue. This isn’t a failure of care - it’s a failure of capacity.Clarion exists to solve this problem at scale. Our AI agents handle the patient journey from end-to-end; from scheduling and rescheduling appointments, to managing referrals and prescription refills. Our AI performs complex workflows with a human-like touch that patients love.We’ve raised $5.5M from Accel, Y Combinator, and Sequoia (Scout), along with founders from Ophelia, Medallion, and Counsel Health. We’re an in-person team based in New York City, moving quickly to ensure every patient gets the care they need.Why Join Us?Solving a real-world challenge: We’re addressing a critical problem that affects millions of patients and providers daily. Our AI agents outperform human schedulers and restore the time needed to focus on patients.Early-stage with strong market validation: We’ve seen 10x revenue growth in the last year alone. We handle millions of interactions for customers ranging from virtual care clinics to a $5B health insurance company.Founding team: Our co-founders bring a deep understanding of the healthcare landscape. Our CEO is a Stanford/Harvard-trained physician and clinical ops leader (Two Chairs, Ophelia), and our CTO is an ex-Amazon Alexa engineer who led AI/ML teams at Salesforce.Outsized early impact: You'll be joining at an early stage where your contributions shape our company's trajectory, processes, and culture, with significant influence on how we grow.In-person collaboration advantage: We've built in-person since day one and maintain this as a strategic advantage. We move faster, build stronger bonds, and create a cohesive culture.What You'll Be Working OnBuild and ship: Write production code—building integrations, configuring AI agents, and implementing platform logic based on customer workflows and scheduling rules.Own implementations end-to-end: Create and manage technical project plans from scoping through go-live. Coordinate internal resources, delegate workstreams, and drive timelines to completion.Engineer our moat: Our competitive advantage is our ability to stay in the weeds with customers until the technology works. You will architect the high-leverage systems and playbooks that transform these complex implementations into a repeatable, scalable infrastructure.Be the technical face to customers: Serve as primary POC for customer technical teams—leading discovery sessions, unblocking integration issues, and building trusted advisor relationships.Optimize AI agents in production: Monitor agent performance at scale, diagnose failure modes, and iteratively refine behavior to improve accuracy, reliability, and patient experience over time.Grow accounts: Drive expansion post-launch by deploying new features, identifying upsell opportunities, and proactively solving emerging pain points.Shape the product: Translate field observations and customer feedback into actionable requirements that inform the product roadmap.RequirementsTechnical foundation: 3+ years of engineering experience shipping production systems while working directly with customers. This is a hands-on coding role, not purely project management.Project leadership: Track record of managing complex, multi-workstream technical projects and coordinating cross-functional resources to deliver on time.Customer-facing presence: Experience as a primary technical POC—comfortable leading architecture discussions and building relationships with technical stakeholders.Product intuition: Ability to synthesize customer needs into insights that bridge field reality and engineering priorities.Interesting Technical ChallengesAI agent tuning at scale: Configure voice agents for medical terminology and complex scheduling logic, then continuously refine as real-world edge cases emerge in production.Workflow orchestration: Map and automate multi-step processes—scheduling, insurance verification, prescriptions, documentation—across diverse customer environments.Personalization that scales: Deploy agents that adapt to each organization's unique protocols and terminology without requiring bespoke rebuilds for every customer.Debugging AI in the wild: Diagnose agent failures across integrations and LLM behavior, then implement fixes that generalize across deployments.Shape the product from the field: As the closest touchpoint to customers, identify patterns across deployments and translate insights into product requirements that drive the roadmap.What we offerDirect mentorship: Work closely with our founding team and experienced leaders who will invest in your professional developmentMeaningful equity: Early employee stock options with significant ownership potentialComprehensive benefits: 100% covered healthcare, flexible time off, commuter benefits, weekly team lunchesTeam culture: Quarterly retreats and monthly team events that build genuine connections in our close-knit NYC teamImpact at scale: Work that builds the infrastructure to help millions of patients access careInterview ProcessAt each stage, we decide within 24hrs and update you shortly after:First Chat (15 min) [Virtual]: A casual conversation about the role and your experience to see if there's a good initial fit.Applied Coding Exercise (1 hr) [Virtual]: Hands-on challenge for building and optimizing AI agents in healthcare.Experience & Culture (30 min) [Virtual]: Deep dive into work style, culture fit, and previous experience.Onsite (Half-day) [In-Person]: Visit our New York office to meet the team, explore our platform, and solve technical problems collaboratively.If you’re ready to be the customer champion that transforms healthcare communication, we’d love to hear from you.

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About CentariAt Centari, we believe that in high-stakes dealmaking, a firm’s competitive edge lies within unlocking its private deal data. Centari is building the deal intelligence platform for the future of law and finance, moving beyond simple automation and into a world of data-driven dealmaking. Our proprietary Deal Reasoning Engine transforms a firm’s goldmine of complex documents into strategic insights, empowering global deal teams to negotiate with the full force of their firm’s collective knowledge.Our team brings together attorneys, financial experts, and engineers across a hybrid, cross-cultural organization. We're backed by top-tier enterprise AI investors including GTMfund, former DoorDash board member Jeremy Kranz, Seamless co-founder Andy Appelbaum, Jack Altman, South Park Commons, and Recall Capital.We are drawn to complexity because that is where true innovation happens. If you’re a builder who thrives in ambiguity and operates with radical ownership, we’d love to meet you.For more information, check out centari.com or find us on LinkedIn.About the RoleWe are hiring a Senior Software Engineer, Backend to join our product team. You'll be a key player in designing and building Centari's core AI technology, working alongside engineers who share a bias for action. As one team, you'll write code, shape the product, interact with customers, and drive initiatives from concept to completion.Our systems are built with Go and React/TypeScript, leveraging cutting-edge LLM technologies across infrastructure, search, and persistence layers. If you're passionate about building impactful LLM applications and thrive on owning complex challenges, we want to hear from you.RequirementsAt least 5+ years of experience building production-ready applications in Go or another strongly typed language.Some experience with or strong interest in LLMs, knowledge graphs, semantic search, and other AI/ML technologies.Proven ability to work with cutting-edge technology and eagerness to learn new skills.Willingness to roll up sleeves and get things done - our engineers are comfortable switching between different technical domains as needed.Strong collaboration skills and ability to work effectively in a fast-paced environment.Experience as a tech lead or driving projects end to end.Nice to haveExperience in enterprise SaaS or with highly regulated industries (e.g., legal, financial services, healthcare).Experience in a startup environment.Specialized experience and skills in either full-stack product development or data/ML infrastructure.What we offerBuild at the frontier of AI for knowledge work, with a highly engaged user base from top firms.Flat organizational structure promoting autonomy and direct impact.Meaningful equity in a high-growth startup.Competitive salary100% remote. Flexible PTO.

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About the RoleMaki is building the AI-powered solution that transforms talent acquisition and talent management. As an AI engineer, you will sit at the intersection of ML research and software engineering. You’ll work on everything from prompt design and evaluation pipelines to integrating AI models into production systems and making them safe, fast, and scalable.Build AI features: Design and implement end-to-end AI features that power Maki’s HR agents, from prototyping to production.Experiment with LLMs: Test, fine-tune, and evaluate cutting-edge models (open-source and commercial) to deliver the best mix of performance, cost, and safety.Develop evaluation pipelines: Build frameworks to measure accuracy, reliability, bias, and business impact of AI-driven features.Optimize for scale: Work on latency, caching, and cost-optimization strategies to make AI features enterprise-ready.Ensure safety & compliance: Collaborate with the security and product teams to ensure AI features meet enterprise standards for privacy, fairness, and reliability.Collaborate cross-functionally: Partner with product managers, designers, and engineers to turn ideas into shipped features.Stay ahead: Explore new AI research, tools, and frameworks to keep Maki at the cutting edge.Who You AreWe’re looking for fast-moving, product-minded full-stack engineers who want to have outsized impact and ownership on a lean, high-performing team. We’re looking for someone who is:Autonomous: You drive projects to completion and thrive in environments where you can take the lead.Forward-Thinking: You are fascinated by the potential of AI and want to be hands-on in applying these technologies.Foundational: You want to be part of a high-growth journey, helping us build our technology and our culture from the ground up.Our tech stack is: Python, OpenAI API, Pytorch, Hugging Face, PostgreSQL, GCP, PoetryWe are optimizing for the best talent and offer competitive compensation to match. If you're excited about redefining the future of AI-powered hiring, we’d love to hear from you!Recruitment ProcessMochi Screening: Experience our product firsthand.Hiring Manager Interview.Technical Discussion.System Design Interview.Final Round with the CEO.

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Forward Deployed AI EngineerThe opportunityWe are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world problems in drug discovery and protein engineering.You will work closely with our customers, understanding their unique technical environments and ensuring that our generative biology platform integrates seamlessly with their systems. You will own the full lifecycle of customer deployments - from initial technical scoping through to production-grade delivery - and act as the voice of the customer back into our product and research teams.Who we areAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.Who you areYou have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field. You have a solid grounding in software engineering principles and modern ML frameworks.You have built systems that access large models via APIs. You have significant experience designing, deploying and maintaining infrastructure for large-scale model serving and have hands-on experience building robust API layers around ML models.You are customer-facing and delivery-oriented. You have direct experience deploying AI systems for external customers. You can translate complex technical concepts into clear language for non-technical stakeholders and thrive in environments where customer success is the primary measure of your work.You are fluent in cloud infrastructure. You have hands-on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.You are a strong communicator and collaborator. You work effectively across functions - with research scientists and business executives alike. You are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations.You are mission driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You thrive in a dynamic, fast-paced environment where priorities can shift and you need to context-switch between multiple customer engagements.What sets you apartYou have experience with bio or protein design models. You have worked on ML-driven projects in computational biology, protein design, or related life science domains. You understand the unique data challenges and evaluation paradigms of biological modelling.You have contributed to generative modelling innovation. You have a track record of novel contributions to generative modelling - whether through publications, open-source work, or impactful product features.You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime. You understand the difference between a prototype and a production system.You have pharma or biotech industry experience. You understand the regulatory landscape, data governance requirements and scientific workflows common in pharmaceutical and biotech organisations.Your responsibilitiesCustomer deployment & integration:Drive the end-to-end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure.Design and build production-grade API integrations, data pipelines and model-serving infrastructure tailored to each customer’s requirements.Work on-site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.Ensure deployments meet enterprise standards for security, performance and reliability.Customer advocacy & product feedback:Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time working on-site at international partner locations as neededGather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.Collaborate with internal teams to shape the product roadmap based on real-world deployment learnings.Create technical documentation, integration guides and best-practice resources for customers.Self development:Stay on top of the latest developments in ML infrastructure, model serving and cloud-native tooling.Gain a strong working understanding of protein and cell biology as it relates to our product.Participate in knowledge sharing, e.g. organise and present at our internal reading group.ApplyWe offer strongly competitive compensation and benefits packages, including:Private health insurancePension contributionsGenerous leave policies (including gender neutral parental leave)Hybrid workingTravel opportunities and moreWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

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Member of Technical Staff, Applied AIThe opportunityWe are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.This is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.Who we areAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.Who you areYou are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.What sets you apart (preferred, not required)You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.Your responsibilitiesDevelop, deploy and adapt our models for customer environments:Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.Ensure deployments meet customer standards for security, performance and reliability.Customer partnership & product feedback:Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.Create technical documentation, integration guides and best-practice resources.Spend time working on-site at international partner locations as needed.Self development:Stay on top of the latest developments in ML, model serving and cloud-native tooling.Gain a strong working understanding of protein and cell biology.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Participate in knowledge sharing, e.g. organise and present at our internal reading group.Attend and present at conferences.ApplyWe offer strongly competitive compensation and benefits packages, including:Private health insurancePension contributionsGenerous leave policies (including gender neutral parental leave)Hybrid workingTravel opportunities and moreWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

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Member of Technical Staff, Applied AIThe opportunityWe are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.This is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.Who we areAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.Who you areYou are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.What sets you apart (preferred, not required)You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.Your responsibilitiesDevelop, deploy and adapt our models for customer environments:Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.Ensure deployments meet customer standards for security, performance and reliability.Customer partnership & product feedback:Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.Create technical documentation, integration guides and best-practice resources.Spend time working on-site at international partner locations as needed.Self development:Stay on top of the latest developments in ML, model serving and cloud-native tooling.Gain a strong working understanding of protein and cell biology.Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Participate in knowledge sharing, e.g. organise and present at our internal reading group.Attend and present at conferences.ApplyWe offer strongly competitive compensation and benefits packages, including:Private health insurancePension contributionsGenerous leave policies (including gender neutral parental leave)Hybrid workingTravel opportunities and moreWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

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About GigaGiga has recently raised a $61M Series A and has several paying customers, including DoorDash. We’re building the next generation of customer experience — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.It’s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:Voice AI startup Giga raises $61M Series ADoorDash and Giga PartnershipGiga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!The RoleWe're looking for new grad engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers.This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.What You'll Work OnYou'll contribute to projects across our stack. Some examples:Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resourcesActivity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behaviorDynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pagesAgent memory: Conversation awareness and recent interaction lookups so agents remember context across sessionsYou'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.You Might Be a Fit If YouAre graduating (or recently graduated) with a CS degree or equivalent backgroundHave internship experience or significant projects where you wrote production-quality codeCan take a problem, figure out an approach, and unblock yourself when you get stuckPrefer shipping over perfection but still care about qualityWant to work at a startup where you'll have real responsibility earlyPerks & BenefitsCatered lunch dailyDinner stipend$150/month wellness benefit (gym, fitness classes, mental health)401(k) planCommuter benefitsMedical, dental, and vision coverageGiga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

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About GigaGiga has recently raised a $61M Series A and has several paying customers, including DoorDash. We’re building the next generation of customer experience — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.It’s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:Voice AI startup Giga raises $61M Series ADoorDash and Giga PartnershipGiga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!The RoleWe're looking for backend engineers to build the infrastructure and systems that power our AI agents. You'll work across the stack, from data pipelines and analytics to real-time agent systems, shipping features that directly impact how our customers operate.This isn't a role where you'll be handed a spec and asked to execute. You'll own problems end-to-end: figuring out the right approach, building it, and iterating based on what you learn.What You'll Work OnA few examples from our current roadmap:Analytics rewrite: Migrating our analytics service to ClickHouse and rebuilding it to scale through our next 10x of growthHallucination detection: Improving our detection systems with the goal of driving hallucination rates toward zeroBrowser use agent: Scaling, stabilizing, and adding features and accuracy to our browser use agent in lieu of formal customer APIsAs a senior engineer, you'll be expected to make sound technical decisions, ship reliably, and help set the bar for code quality and system design. You'll have significant autonomy and influence over what gets built and how.Tech StackBackend: Python (Django/FastAPI), TypeScript (Node.js)Infrastructure: AWS, Modal, Kubernetes, PostgresFrontend: TypeScript, Next.js (you'll interact with this, but it's not the focus)You Might Be a Fit If YouHave 4+ years building backend systems, ideally at companies where reliability and scale matteredAre comfortable with ambiguity: you can take a loosely-defined problem and figure out what to buildYou'll jump into unfamiliar parts of the codebase when that's what the problem requiresWrite clean code and care about getting the details right, but also know when to shipWant to work on hard problems with a small team where your work has obvious impactAre excited about AI agents and the infrastructure challenges that come with running them in productionPerks & BenefitsCatered lunch dailyDinner stipend$150/month wellness benefit (gym, fitness classes, mental health)401(k) planCommuter benefitsMedical, dental, and vision coverageGiga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

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About GigaGiga has recently raised a $61M Series A and has several paying customers, including DoorDash. We’re building the next generation of customer experience — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.It’s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:Voice AI startup Giga raises $61M Series ADoorDash and Giga PartnershipGiga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!The RoleWe're looking for software engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers who will help you grow.This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.What You'll Work OnYou'll contribute to projects across our stack. Some examples:Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resourcesActivity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behaviorDynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pagesAgent memory: Conversation awareness and recent interaction lookups so agents remember context across sessionsAs an early-career engineer, you'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.You Might Be a Fit If YouHave 1-3 years of professional software engineering experienceAre curious and ask good questions—you want to understand why things work, not just howCan take feedback well and iterate quicklyPrefer shipping over perfection but still care about qualityWant to grow at a startup where you'll have real responsibility earlyPerks & BenefitsCatered lunch dailyDinner stipend$150/month wellness benefit (gym, fitness classes, mental health)401(k) planPaid parental leave (12 weeks maternal, 6 weeks paternal)Commuter benefitsMedical, dental, and vision coverageGiga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is accelerating the future of AI and high-performance compute by building industry-leading CPU and AI architectures. As an Automotive and Robotics SoC Architect, you will define scalable, top-down system architectures that unify our CPU and AI technologies for next-generation automotive applications. This senior technical role shapes the architectural direction of our automotive and robotics portfolio, ensuring our products meet the industry's highest expectations for performance, safety, reliability, and security. This position is central to how Tenstorrent delivers world-class automotive solutions and requires strong technical leadership, systems thinking, and cross-functional collaboration. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are A systems thinker who can architect complex SoCs from concept to execution. A strong communicator who can articulate technical direction across engineering teams and external partners. Someone with deep knowledge of safety-critical systems and the unique needs of automotive environments. An innovator who can identify future use cases and propose next-generation architectural solutions. A leader who thrives in a highly technical, cross-functional, fast-moving environment.   What We Need Bachelor’s, Master’s, or Ph.D. in Electrical Engineering, Computer Engineering, or related field. Extensive experience designing complex SoCs, ideally in automotive applications. Proficiency in hardware description languages such as Verilog or VHDL. Experience with hardware/software co-design and co-verification. Knowledge of automotive safety standards (e.g., ISO 26262) and security principles. Someone comfortable with up to 25% international travel.  Experience with both cameras, sensors, and others is a plus.   What You Will Learn How cutting-edge CPU and AI architectures are adapted for automotive-grade environments. Best-in-class methodologies for safety-critical SoC design, verification, and system integration. How to translate emerging automotive use cases into scalable, future-proof SoC architectures. Approaches to hardware-level security, robustness, and cyber-resilience in automotive compute systems. Cross-functional collaboration strategies that drive innovation across architecture, software, DV, and product teams.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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Hi, we're The Browser Company 👋 and we're building a better way to use the internet. Browsers are unique in that they are one of the only pieces of software that you share with your parents as well as your kids. Which makes sense, they're our doorway to the most important things — through them we socialize with loved ones, work on our passion projects, and explore our curiosities. But on their own, they don’t actually do a whole lot, they’re kind of just there. They don’t help us organize our messy lives or make it easier to compose our ideas. We believe that the browser could do so much more — it can empower and support the amazing things we do on the internet. That’s why we’re building one: a browser that can help us grow, create, and stay curious. To accomplish this lofty task, we’re building a diverse team of people from different backgrounds and experiences. This isn’t optional, it’s crucial to our mission, as we need a wide range of perspectives to challenge our assumptions and shape our browser through a bold, creative lens. With that in mind, we especially encourage women, people of color, and others from historically marginalized groups to apply.About the RoleBuilding software is changing. With modern AI coding tools and automated reviewers, the bottlenecks in shipping products are shifting from “how fast can you type” to “how have you designed the system that writes, reviews, and ships the code.” At The Browser Company, we believe this shift is so profound that how we build is as important, and ultimately as defensible, as what we build.We’re investing deeply in “building how we build”: an AI‑native development stack that turns our way of working into compounding leverage for every engineer and team. Our vision is a world where most code is generated and reviewed by AI, where model training and prompt optimization are automated, and where product builders operate at a higher layer—seeing trends, deciding what to build, and clicking the “right” buttons rather than hand‑crafting every line.As our Technical Lead for Developer Experience at Browser Company, you won’t just maintain tools or CI pipelines–you’ll lead the creation of a second product: an internal, AI‑powered software generation and review platform that changes how Dia gets built.Overall you will...Design and lead the “build how we build” platform: an internal SaaS‑like experience where engineers and non‑engineers can describe what they want, and our system realizes the rest.Partner with AI and infra teams to wire together the pieces we already have—AI coding tools, virtualized environments, CI, AI code reviewers, evals, and prompt and model optimization—into a cohesive, opinionated product that our teams love to use.Define success metrics for this platform and iterate quickly based on real usage and feedback from our engineers.Turn our DevEx stack into true leverage, so that every engineer and PM can move with 10x more impact.Qualifications5+ years of experience with developer tools and build environments, open-source developer tooling, or low-level systems experience.Experience owning a zero‑to‑one product or platform, ideally in a role with founder‑like autonomy (founder/CTO, tech lead, staff/principal on a platform or DevEx team).You're passionate about building tools and systems that make other engineers more productive and strive to make them elegant and maintainable.You thrive in a high‑trust, high‑ambiguity environment: you seek feedback, but you don’t need hand‑holding.We’re primarily focused on hiring in North American time zones and require that folks have 4+ hours of overlap time with team members in Eastern Time Zone.Compensation and BenefitsOur total compensation package for full-time employees includes base salary, equity, and benefits. The annual salary range for this role is $290,000 - $340,000 USD. The actual salary offered will vary based on experience level and interview performance.Benefits: We offer a wide range of perks and benefits designed to support you, your family, and help you engage with your local community. To learn more, visit go.atlassian.com/perksandbenefits.Location: We’re a remote-friendly company and can hire in any country where Atlassian has a legal entity. If you live in New York (or want to visit), you’re welcome to work from our beautiful office in Williamsburg.The Browser Company is an ambitious team of close to 100 people (and growing!) who are passionate about building great products. We are a remote-first, distributed team, with the option to work from office in Brooklyn, New York. We strongly support diversity and encourage people from all backgrounds to apply.  🚙 To read more about what we value as a company, check out Notes on Roadtrips on our blog.