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About Cantina:Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!About the Role:We are looking for an Applied ML Engineer to build and scale the data pipelines behind our large video generation models. This role is focused on collecting large amounts of relevant video data, preparing high-quality training samples, and developing robust preprocessing, filtering, and parsing workflows. You'll orchestrate annotation pipelines across platforms such as MTurk and own the full lifecycle of training data, from raw ingestion to clean, model-ready samples that directly drive quality improvements. This role sits at the intersection of data engineering and ML research, making it central to how we turn messy real-world data into the fuel that moves our models forward.What You’ll Do:Build and maintain data pipelines for large video generation models, including data ingestion, parsing, filtering, preprocessing, and dataset curation at scale, using tools such as AWS S3 and DynamoDB.Design and run annotation workflows across platforms such as MTurk, Prolific, and Mechanical Turk, including task design, quality control, and label validation.Train, evaluate, and improve smaller supporting models used for data filtering, quality assessment, preprocessing, or other parts of the ML pipeline.Partner closely with research and engineering teams to turn experimental workflows into scalable, repeatable systems that support model training and evaluation.Own data quality across the pipeline by identifying bottlenecks, failure modes, and low-quality sources, and continuously improving tooling and processes.Build internal tools and automation that make it easier to prepare datasets, launch annotation jobs, monitor outputs, and support model development end to end.Drive larger pipeline projects from start to finish, such as new dataset creation efforts or upgrades to labeling and preprocessing infrastructure.Work within a Kubernetes-based training infrastructure, ensuring datasets are properly prepared, formatted, and delivered to training clusters.Profile and optimize research model inference scripts used in preprocessing steps, ensuring that model-driven filtering and transformation stages run within practical time and cost constraints when applied to large-scale raw data.What You’ll Bring:3+ years of experience in machine learning, applied ML, data pipelines, or related engineering roles, ideally working on large-scale multimodal, video, or vision-based systems.Strong programming skills in Python and solid experience building reliable data processing and preprocessing pipelines for ML workflows.Hands-on experience preparing training data for ML models, including parsing, filtering, dataset curation, quality control, and large-scale data handling using tools such as AWS S3 and DynamoDB.Familiarity with annotation and labeling workflows, including task design, vendor or crowd-platform orchestration such as MTurk or Prolific, and methods for ensuring label quality.Experience working with Kubernetes for orchestrating distributed workloads, including data preprocessing, pipeline execution, and dataset delivery to training clusters.Comfort working across cloud and on-demand compute environments such as AWS and RunPod, with the ability to port and optimize pipelines across infrastructure.Familiarity with distributed data processing frameworks and experience designing systems that operate reliably at scale across many nodes or workers.Working knowledge of PyTorch and the broader deep learning stack, with the ability to read, debug, and optimize research model inference code for use in production preprocessing pipelines.Ability to work cross-functionally with research and engineering teams and translate experimental ideas into robust, scalable systems.Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Engineering, Mathematics, or a related technical field; experience in generative video, computer vision, or multimodal ML is strongly preferred.Bonus: Experience training, evaluating, or fine-tuning smaller ML models used for classification, filtering, ranking, quality assessment, or other supporting tasks in an ML pipeline.Compensation:The anticipated annual base salary range for this role is between $200,000-$260,000 (€170,000-€225,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.Benefits for U.S.-based roles: Competitive salary and generous company equityMedical, dental, and vision insurance – 99.99% of premiums covered by Cantina42 days of paid time off, including:15 PTO days10 sick days15 company holidays2 floating holidaysGenerous parental leave & fertility support401(k) retirement savings planLifestyle spending account – $500/month to use however you’d likeComplimentary lunch and snacks for in-office employeesOne Medical membership, and more!

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We are looking for the best42dot의 Senior Computer Vision Engineer는 안전한 자율주행 기술들을 연구 개발합니다. 고도화된 컴퓨터비전과 기계학습 기술을 활용하여 자율주행차에서 취득되는 다양한 시각정보들을 처리하고, 사람 수준의 자율주행 인식 기능을 구현합니다.As a Senior Computer Vision Engineer at 42dot, you will focus on researching and developing advanced autonomous driving technologies. Utilizing sophisticated computer vision and machine learning techniques, you will process various visual data acquired from autonomous vehicles and implement human-level autonomous driving perception capabilities.Responsibilities 자율주행 기술구현을 위한 3차원 컴퓨터비젼 및 기계학습 알고리즘 연구 개발3D shape modeling and processingObject pose estimation and trackingEfficient and scalable visionVision and roboticsLow-level and physics-based visionSelf-supervised representation learning from large-scale unlabeled scene dataWorld models and closed-loop simulation for autonomous drivingConduct research and develop 3D computer vision and machine learning algorithms for integrating autonomous driving technologyPerform 3D shape modeling and processing tasksImplement object pose estimation and tracking algorithmsDevelop efficient and scalable vision solutionsExplore the intersection of vision and roboticsWork on low-level and physics-based vision algorithmsSelf-supervised representation learning from large-scale unlabeled scene dataWorld models and closed-loop simulation for autonomous drivingQualifications 유관 경력 7년차 이상컴퓨터비젼, 로보틱스, 또는 기계학습과 관련된 전공의 석사/박사 학위 이상 혹은 동등한 경력컴퓨터비젼 및 기계학습에 대한 이론 및 실무 지식뛰어난 프로그래밍 기술(C/C++, Python 등)Master’s (MS) or Ph.D. in Computer Vision, Robotics, Machine Learning, or a related field7+ years of relevant experience or equivalent practical experienceStrong theoretical and practical knowledge of computer vision and machine learning algorithmsProficiency in programming languages such as Python and C/C++Preferred Qualifications 자율주행 및 로보틱스 관련 연구 개발 경험GPS, IMU, 카메라, LIDAR 와 같은 다양한 센서를 사용한 개발 경험VR/AR 관련 어플리케이션 개발 경험병렬 프로그래밍 및 시스템 최적화 관련 개발 경험관련 분야 저서/학술활동 이력(CVPR, ICCV, ECCV, IJCV, TIP, TPAMI 등)Proven experience in projects or commercial systems related to autonomous driving, robotics, or 3D visionHands-on experience with multi-sensor data processing and fusion (GPS, IMU, cameras, LiDAR)Expertise in parallel programming (e.g., CUDA, OpenCL) and system optimizationDemonstrated experience in SLAM, depth estimation, 3D reconstruction, or pose estimation algorithm designExperience in developing VR/AR applicationsStrong academic background with publications in conferences/journals such as CVPR, ICCV, ECCV, TPAMI, or IJCVExperience deploying and managing ML models in large-scale cloud environmentsInterview Process 서류전형 - 코딩테스트 - 화상면접 (1시간 내외) - 대면 혹은 화상면접 (3시간 내외) - 최종합격전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.Resume Screening - Coding Test - Virtual Interview (approximately 1 hour) - Onsite or Virtual Interview (approximately 3 hours) - Final OfferPlease note that the interview process may vary depending on the position and is subject to change based on scheduling and other circumstances.Interview schedules and results will be communicated individually via the email address provided in your application.Additional Information 모든 제출파일은 PDF 양식으로 업로드를 부탁드립니다.국가보훈대상자 및 취업보호대상자는 관계법령에 따라 우대합니다.장애인 고용촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.42dot은 의뢰하지 않은 서치펌의 이력서를 받지 않으며, 요청하지 않은 이력서에 대해 수수료를 지불하지 않습니다.Please upload all required documents in PDF format.Veterans and applicants eligible for employment protection will receive preferential consideration in accordance with applicable laws and regulations.In compliance with the Act on Employment Promotion and Vocational Rehabilitation for Persons with Disabilities, registered individuals with disabilities will receive preferential consideration.42dot does not accept unsolicited resumes from search firms. We will not pay any fees for resumes submitted without prior agreement.※ 지원 전 아래 내용을 꼭 확인해 주세요.※ Please make sure to review the information below before applying.42dot이 일하는 방식, 42dot Way 보러가기 →Learn more about how we work at 42dot, 42dot Way →42dot만의 업무몰입 프로그램, Employee Engagement Program 보러가기 →Explore 42dot’s unique Employee Engagement Program, Employee Engagement Program →

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Product Engineer — SearchYou'll own the developer-facing search experience at Firecrawl — taking the retrieval and ranking improvements coming out of research and shipping them as a product developers can't stop using. This isn't a pure research role and it isn't a pure backend role. You sit at the intersection: you understand how the systems work deeply enough to improve them, and you care about how they feel to use obsessively enough to make them great. At a 26-person company, the gap between research and shipped product is exactly one person. You're that person.Salary Range: $180,000–$290,000/year (Range shown is for U.S.-based employees. Compensation outside the U.S. is adjusted fairly based on your country's cost of living. You can explore how we calculate this here: https://www.firecrawl.dev/careers/compensation.)Equity Range: Up to 0.15%Location: San Francisco, CA or Remote (Americas, UTC-3 to UTC-10)Job Type: Full-TimeExperience: 3+ years in applied RL, ML engineering, or model training — with production systemsVisa: US Citizenship/Visa required for SF; N/A for RemoteAbout FirecrawlFirecrawl is the easiest way to extract data from the web. Developers use us to reliably convert URLs into LLM-ready markdown or structured data with a single API call. In just a year, we've hit 8 figures in ARR and 100k+ GitHub stars by building the fastest way for developers to get LLM-ready data.We're a small, fast-moving, technical team building essential infrastructure superintelligence will use to gather data on the web. We ship fast and deep.What You'll DoShip search improvements that developers notice. Take retrieval and ranking improvements from research and turn them into product changes that make developers say "this just works." You know that a 200ms latency improvement isn't just a benchmark win — it's a better product. You ship the whole thing: the API change, the docs update, the example that makes it obvious.Own the search API end-to-end. You're responsible for how Firecrawl's search endpoint feels to integrate, use, and build on. That means response format, latency, error handling, pagination, filtering — every surface a developer touches. You're the person who notices when something is confusing before a user files a GitHub issue about it.Dogfood relentlessly. You build things with the API before you ship them. You feel the friction before your users do. You read every GitHub issue, every Discord thread, every support ticket that touches search — not because someone asked you to, but because that's where the product signal lives.Translate research into product decisions. You work closely with the Search/IR and RL Research Engineers. You understand their work well enough to make good product calls about what to prioritize, what to expose to users, and what to keep under the hood. You ask good questions. You push back when something technically elegant would make the API worse.Run fast product experiments. You form a hypothesis about what would make search better for developers, instrument it, ship it, measure it, and decide quickly. You're comfortable making calls with imperfect data because waiting for perfect data means shipping nothing.Raise the bar on developer experience. Firecrawl's users are technical. They have high standards. They notice when response formats are inconsistent, when error messages are unhelpful, when documentation doesn't match behavior. You notice too — and you fix it before they have to ask.What We're Looking ForObsessive about developer experience. You think about DX the way a designer thinks about pixels. Latency, response structure, error messages, API ergonomics — these things matter to you on a visceral level. You've built APIs that developers loved and you know the difference between an API that works and one that delights.Speaks both product and engineering fluently. You can read a ranking algorithm and understand its implications for the search experience. You can write the API spec and implement it yourself. You don't need a PM to tell you what matters or an ML engineer to explain why a retrieval change is significant. You connect those dots on your own.Hands-on builder who ships. You write code. You own features from design to deployment. You're comfortable with ambiguity and you don't need a perfectly scoped ticket to make progress. You ship something, learn from it, and iterate.Has a feel for search as a product. You've thought seriously about what makes search good — not just fast or accurate, but genuinely useful. You understand the difference between recall and precision and why developers care about both. You have intuitions about query understanding, result ranking, and when semantic search beats keyword search — and you've built products that put those intuitions to work.Brings production instincts. You've operated systems under real load. You know what breaks first, how to instrument what matters, and how to make good latency/quality tradeoffs. You're not just building features — you're building infrastructure developers depend on.Backgrounds that tend to do well: Engineers who've owned search or discovery features at developer-tools companies. Full-stack engineers with a strong backend bias who've shipped APIs used by thousands of developers. Engineers from search infrastructure teams who got frustrated by the distance between their work and the user experience. People who've built on top of Elasticsearch, Vespa, or vector databases — and cared enough about the product layer to go deeper than the query interface.What We're NOT Looking ForGreat engineers who don't care about DX. If you build technically excellent systems but think API ergonomics and documentation are someone else's problem, this isn't the role. The product experience is part of the job — not an afterthought.People who need a PM. There's no product manager between you and the work. You define what good looks like, you decide what to prioritize, and you own the outcome. If that's uncomfortable, you'll struggle here.Specialists who only work on one layer. If you're only interested in backend systems and tune out when the conversation shifts to how something is exposed to developers — or vice versa — this won't be a fit. This role requires you to hold both.Slow shippers. The research team will produce improvements faster than a slow product cycle can absorb them. We need someone who can take something from "this ranking model is better" to "this is live in the API with docs and an example" in days, not sprints.People who don't use the product. If you're not the kind of engineer who builds side projects with APIs like ours, reads the docs critically, and notices when something feels off — you'll miss the signal that makes this role work.A Note On PaceWe operate at an absurd level of urgency because the window for what we're building won't stay open forever. If that excites you, keep reading. If it doesn't, no hard feelings — but this role probably isn't for you.Benefits & PerksAvailable to all employeesSalary that makes sense — $180,000–$290,000/year, based on impact, not tenureOwn a piece — Up to 0.15% equity in what you're helping buildGenerous PTO — 15 days mandatory, anything after 24 days, just ask (holidays excluded); take the time you need to rechargeParental leave — 12 weeks fully paid, for moms and dadsWellness stipend — $100/month for the gym, therapy, massages, or whatever keeps you humanLearning & Development — Expense up to $1,000/year toward anything that helps you grow professionallyTeam offsites — A change of scenery, minus the trust fallsSabbatical — 3 paid months off after 4 years, do something fun and newAvailable to US-based full-time employeesFull coverage, no red tape — Medical, dental, and vision (100% for employees, 50% for spouse/kids) — no weird loopholes, just care that worksLife & Disability insurance — Employer-paid short-term disability, long-term disability, and life insurance — coverage for life's curveballsSupplemental options — Optional accident, critical illness, hospital indemnity, and voluntary life insurance for extra peace of mindDoctegrity telehealth — Talk to a doctor from your couch401(k) plan — Retirement might be a ways off, but future-you will thank youPre-tax benefits — Access to FSAs and commuter benefits (US-only) to help your wallet out a bitPet insurance — Because fur babies are family tooAvailable to SF-based employeesSF HQ perks — Snacks, drinks, team lunches, intense ping pong, and peak startup energyE-Bike transportation — A loaner electric bike to get you around the city, on usInterview ProcessApplication Review — Send us your work and a quick note on why this excites you. Show us what you've shipped — search features, APIs, developer-facing products. A GitHub link, a product you've built, or a write-up of something you're proud of goes a long way.Intro Chat (~20 min) — A quick conversation to get to know each other before we go deep. We'll talk about what you've been working on, what drew you to Firecrawl, and what you're looking for in your next role. Time for your questions too.Technical Deep Dive (~60 min) — Go deep on search products and APIs you've built: architecture decisions, DX tradeoffs, how you've translated technical improvements into product changes. We'll explore a live problem — how you'd take a retrieval improvement and ship it as a better developer experience at Firecrawl. We're looking for product instincts, technical depth, and the ability to hold both at once.Founder Chat (~30 min) — Culture, pace, ownership, and how you like to work. Time for your questions too.Paid Work Trial (1–2 weeks) — Tackle a real search product problem with production implications. We evaluate on shipping speed, product judgment, and how well you balance technical quality with developer experience.Decision — We move fast after the trial.If you want to own the search experience at one of the fastest-growing developer infrastructure companies in AI — and you're the kind of engineer who won't stop until it's great — this is your shot.👉 Apply now.

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We are looking for a New Grad, Full Stack Engineer to become part of our mission focused and high performing engineering team, and work closely with colleagues in Ankara, Berlin and our Silicon Valley Headquarters, to drive meaningful AI product innovation at massive scale.The Mission: TrustLab is building the trust and safety layer that enables AI agents to be deployed responsibly, as well as other scalable AI solutions, at global scale. We develop and deploy advanced autonomous AI systems that monitor, evaluate and observe agents during development and in production. Founded by senior leaders from Google, YouTube, TikTok, and Reddit, TrustLab’s solutions are industry leading and used by global technology brands to support their daily operations.The Impact: You are part of a team that is responsible for some of the most critical components of our AI centric tech stack. You contribute to building parts of our global platform that evaluates cutting edge customer AI systems at scale. You will work closely with experienced engineers to push the boundaries of what’s possible with state of the art AI tech, while learning and growing in a high-impact environment.The Role We’re looking for a Backend Engineer to help build high-performance backend systems that support AI-driven workflows and large-scale data processing. You’ll work on distributed services, APIs, and core infrastructure powering mission-critical products. This role requires strong backend fundamentals, Python experience, and a willingness to learn how to think in systems, not just endpoints.What You’ll DoBuild and maintain backend services in PythonContribute to APIs and microservices with clean, maintainable abstractionsWork with datasets and asynchronous processing pipelinesImprove performance, reliability, and observabilityParticipate in system design discussions and learn from senior engineersCollaborate closely with frontend and AI/ML engineersWrite production-quality, testable, secure codeParticipate in code reviews and continuously improveWhat We’re Looking ForCore Requirements0–2 years of backend engineering experienceExperience with Python (FastAPI, Django, Flask, or similar)Basic understanding of REST APIs and backend development principlesFamiliarity with databases (PostgreSQL, MySQL)Eagerness to learn system design, scalability, and performanceBonus points:Exposure to AWS or another cloud providerInterest in AI/ML systems or data-intensive applicationsHow We Work:Small teams, high ownership, minimal process overheadAsync-first collaboration across Ankara and Silicon ValleyEngineers are involved in product and technical decisions, not just executionWhy Join TrustLab Ankara? Foundry of Experts: Work directly with AI Industry leaders who scaled trust & safety systems at the world’s largest platforms. Competitive Compensation: Annual salary range of $40k–$45k USD, plus meaningful equity in a venture-backed startup. Modern Workspace: Hybrid flexibility with in-person collaboration at our Maidan, Ankara office. Substantial benefits incl. paid supplemental private health insurance, education stipend, meals and more. Annual Paid US Offsite: Opportunity to join the full team at our US headquarters for strategy alignment, deep collaboration, and innovation.

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TL;DR: We're looking for a Senior Product Manager to lead the Lovable agent end-to-end - owning quality, roadmap, and the feedback loops that make it better. You'll shape how our agent reasons, acts, and delivers for millions of users, directly influencing one of the most consequential product surfaces at Lovable.Why Lovable? Lovable lets anyone and everyone build software with any language. From solopreneurs to Fortune 100 teams, millions of people use Lovable to transform raw ideas into real products - fast. We are at the forefront of a foundational shift in software creation, which means you have an unprecedented opportunity to change the way the digital world works. Over 2 million people in 200+ countries already use Lovable to launch businesses, automate work, and bring their ideas to life. And we're just getting started. We're a small, talent-dense team building a generation-defining company from Stockholm. We value extreme ownership, high velocity, and low-ego collaboration. We seek out people who care deeply, ship fast, and are eager to make a dent in the world.What we're looking for6+ years in the software industry, with direct ownership of an AI or LLM-powered product in a product management or engineering leadership roleHands-on experience building and shipping agent-based systems - you understand tool use, planning loops, multi-step reasoning, and how agents failTechnical fluency: you program or have programmed, and can read model outputs, traces, and evals with confidenceStrong product sense and systems thinking - you know when to move fast and when to invest in foundational work, and you have sharp opinions on how agents should communicate, recover from errors, and earn user trustPreferred: Deep familiarity with prompt engineering and evaluation frameworks; prior experience operating at the frontier where best practices are still being writtenWhat you'll doRepresent the user - synthesize findings on agent performance and behavior, and bring them to the team with clarity and convictionRun discovery end-to-end: user interviews, competitive research, eval analysis, prompt experimentation, and crafting messaging for upcoming agent capabilitiesOwn the quality bar for agent outputs - drive eval infrastructure, monitor regressions, and ensure the agent improves with every releaseScope ruthlessly - ship the right slice of functionality, validate what works through user feedback and metrics, and cut what doesn'tEnable sales, support, and marketing with the context they need to communicate new agent capabilities effectivelyProjects you'll tackle first: Rebuilding the agent evaluation framework to catch regressions before they ship; running discovery on the biggest gaps in agent reliability and trust; defining and shipping the first iteration of improved agent error recovery and communicationAbout your application Please submit your application in English. It's our company language, so you'll be speaking lots of it if you join. We treat all candidates equally - if you're interested, please apply through our careers portal.

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About BreeBree is a consumer finance platform building faster, simpler, and more affordable financial services for Canadians who often live paycheck to paycheck. We operate in a massive market that’s historically been underserved by traditional financial institutions, and we’re building products that help customers access short-term credit with a transparent, user-first experience.To date, 800,000+ Canadians have signed up for Bree—and we believe we’re still early. We’re at an exciting intersection of product-market fit, rapid growth, and a clear path to becoming one of the most important fintech companies in Canada.We’re at 8-figures of annualized revenue, growing quickly, and profitable. We were part of Y Combinator (Summer 2021) and raised a $2M seed round shortly after.About the RoleWe’re looking for a Machine Learning Engineer to build and scale high-impact, world-class ML systems. You’re passionate about deploying AI solutions, optimizing performance, and driving measurable results. Your work will power critical decisions and shape the future of our technology.What You'll DoDesign, develop, and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation, and inference.Implement MLOps best practices, including CI/CD for ML models, model versioning, monitoring, and retraining strategies.Optimize ML models using feature engineering, hyperparameter tuning, and scalable inference techniques.Work with structured and unstructured data, leveraging Pandas, NumPy, and SQL for efficient data manipulation.Apply machine learning design patterns to build modular, reusable, and production-ready models.Collaborate with data engineers to develop high-performance data pipelines for training and inference.Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and orchestration tools like Docker and Kubernetes.Maintain model performance by implementing continuous monitoring, bias detection, and explainability techniques.What You'll NeedProficiency in Python and familiarity with ML libraries like Scikit-learn, LightGBM, and PyTorch.Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for tracking experiments and automating workflows.Hands-on experience with data manipulation libraries (Pandas, NumPy) and databases (SQL, NoSQL).Knowledge of cloud-based ML deployment and infrastructure management.Ability to implement real-time and batch inference pipelines efficiently.Strong analytical and problem-solving skills to translate business needs into scalable ML solutions.Eagerness to work in a fast-paced environment and continuously refine ML processes for efficiency and accuracy.BenefitsTop of the market compensation for top performersComprehensive dental / vision$1,500 annual learning stipend$1,000 annual wellness stipend$250 monthly lunch stipend2 annual company retreatsParental leaveUnlimited PTO

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About Rad AIAt Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI.Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked by Deloitte as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 list, highlighting the innovation and momentum behind our mission.If you’re ready to shape the future of healthcare, we’d love to have you on our team!Rad AI is on a mission to make radiologists' lives better and patient care smarter. Our AI-powered software helps radiology groups work more efficiently, communicate more clearly, and deliver more consistent, higher-quality reports. We're a team of people who care deeply about what we build and about the clinicians and patients whose lives depend on it. We'd love to have you join us.Why We Need YouA radiology report is the moment the entire diagnostic process culminates. It's where a radiologist's expertise becomes actionable insight for the ordering physician, for the care team, for the patient. At Rad AI, our Reporting product is the heart of what we do. It's where our AI meets the real world.The engineering team behind that product doesn't just ship features, they shape what radiologists experience every single day. When that experience is excellent, we earn trust, and trust is everything in healthcare. When it falls short, it's not just a bug or a missed deadline; it's a radiologist losing faith in AI at the exact moment they needed it most.That's why we need you. You're the person who holds the standard and ensures that the team building our most important product is doing the best work of their careers. Your leadership is what turns a group of talented engineers into a cohesive force that ships software radiologists love. Without someone exceptional in this role, we can't build the Reporting product our customers deserve. And without that product, Rad AI doesn't win.Here's What You'll be DoingYou'll lead the engineering team responsible for our Reporting product — the flagship of Rad AI's platform. That means owning the technical strategy for the product, partnering closely with Product and Design to shape the roadmap, and making sure your team has everything they need to build, ship, and iterate with confidence. You'll be equally at home diving into an architectural decision and coaching an engineering manager through a hard conversation.This is a leadership role, but you're not removed from the work; you're in it. You'll set the technical bar, model the culture you want to see, and be the person your team looks to when things are hard and the stakes are high.In addition, you'll:Build and lead a team of engineers and engineering managers, hiring exceptional people and developing them into their best selves.Own the technical architecture of our Reporting product, making consequential decisions about scalability, reliability, and long-term maintainability.Partner with Product, Design, and Clinical teams to translate complex customer needs into elegant, impactful engineering solutions.Drive a culture of technical excellence by setting high standards for code quality, system design, and engineering practices without letting perfection be the enemy of shipping.Serve as a key voice in company-wide engineering strategy, representing the Reporting team at the leadership level.Who We're Looking ForYou have 10+ years of software engineering experience and at least 5 years leading engineering teams, including direct experience managing other managers.You've shipped and scaled a complex software product end-to-end, and you can point to specific decisions you made that were critical to its success.You've built and grown high-performing engineering teams; people you've managed have gone on to do great things, and they'd work with you again.You have deep experience with data-intensive applications, including reporting, analytics, or data visualization products.It Would Be Nice IfYou've worked in a healthcare technology or other regulated industry environment and understand the unique challenges that come with it.You have hands-on experience with AI or ML-powered products, and you're excited about what that means for the future of clinical software.You've led engineering at a high-growth startup and thrived in the ambiguity that comes with it.Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care—making a meaningful impact on millions of lives. Driven by our mission,  we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you!To learn more about what it's like to work at Rad AI, visit https://www.radai.com/life-at-rad-ai and be sure to follow us on LinkedIn to stay up to date!For US-Based Full-Time Roles, Rad AI offers a variety of benefits, including:Comprehensive Medical, Dental, Vision & Life insuranceHSA (with employer match), FSA, & DCFSA 401(k)11 Paid Company HolidaysLocation FlexibilityFlexible PTO policyAnnual company-wide offsitePeriodic team offsitesAnnual equipment stipendFor roles based outside the US, your recruiter can share more detailsAt Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @radai.com or no-reply@ashbyhq.com.

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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 Agent Engineering team at Decagon deploys mission-critical AI agents to our customers that impact millions of users and directly drive Decagon’s growth. You will build on our industry-leading AI agent platform, collaborate directly with customers and use your own creativity to devise long-term, scalable solutions.Our mission is to deliver magical support experiences — AI agents working alongside human agents to help users resolve their issues.About the RoleOn the Agent Engineering team, you’ll have complete ownership and autonomy in building and shipping best-in-class AI agents, from initial implementation through continuous iteration. You’ll work directly with leaders across industries like finance, healthcare and hospitality, solving their users’ needs with reliable and intuitive AI agents.Engineers here own their work end-to-end and are trusted to make a real impact. This role is for someone who dives deep into complex system challenges and builds elegant solutions that scale to millions of users.In this role, you willDesign and build AI agents that outperform human agents in managing complex customer interactions and driving customer retentionIdentify cross-customer trends that guide the evolution of Decagon’s agent building platform and research effortsExperiment with and run evaluations on the latest text and voice models, then integrate them at scale with large enterprise-grade customersYour background looks something like thisHave 5+ years of industry experience in software engineeringProficiency with Python, Typescript and asynchronous programmingA high degree of comfort digging into system failures within deep technology stacks using any tool necessaryEven betterPrior experience working with multi-modal modelsBenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation$250K – $350K + Offers Equity

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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 Agent Engineering team at Decagon deploys mission-critical AI agents to our customers that impact millions of users and directly drive Decagon’s growth. You will build on our industry-leading AI agent platform, collaborate directly with customers and use your own creativity to devise long-term, scalable solutions.Our mission is to deliver magical support experiences — AI agents working alongside human agents to help users resolve their issues.About the RoleOn the Agent Engineering team, you’ll have complete ownership and autonomy in building and shipping best-in-class AI agents, from initial implementation through continuous iteration. You’ll work directly with leaders across industries like finance, healthcare and hospitality, solving their users’ needs with reliable and intuitive AI agents.Engineers here own their work end-to-end and are trusted to make a real impact. This role is for someone who dives deep into complex system challenges and builds elegant solutions that scale to millions of users.In this role, you willDesign and build AI agents that outperform human agents in managing complex customer interactions and driving customer retentionIdentify cross-customer trends that guide the evolution of Decagon’s agent building platform and research effortsExperiment with and run evaluations on the latest text and voice models, then integrate them at scale with large enterprise-grade customersYour background looks something like thisHave 5+ years of industry experience in software engineeringProficiency with Python, Typescript and asynchronous programmingA high degree of comfort digging into system failures within deep technology stacks using any tool necessaryEven betterPrior experience working with multi-modal modelsBenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation$250K – $330K + Offers Equity

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V7At V7, we’re building AI platforms that help humans do their best work, at incredible scale and speed. Our mission is to turn human knowledge into trustworthy AI, making complex tasks faster, smarter, and more accurate. We’re growing fast, backed by leading investors and AI pioneers (including the minds behind Transformers and Gemini). The ProductV7 Go provides legal, finance, insurance, and accounting teams with a toolkit for deploying and building custom no-code AI agents. The platform focuses taking multi-modal data and delivering verifiable outputs with transparent AI logic to ensure accuracy and compliance.V7 Go supports all of the latest models like GPT, Claude, and Gemini for the best accuracy and performance.⁠⁠⁠⁠ Watch the V7 Go keynote to see what we’re building.The team you’ll be joining and the impact you’ll haveYou'll join our go-to-market team as our second Solutions Engineer in New York (the team is six people), sitting at the intersection of sales and product in a company processing tens of millions of documents for customers across finance, insurance, and real estate.V7 Go 4x-ed revenue last year, with 160%+ upsell into accounts. You'll help accelerate that trajectory by making sure every customer gets real value.We run a lean, high-trust team where you'll work directly with AEs, engineers, and product to close complex deals and turn new logos into long-term champions.Your work directly shapes how enterprises experience agentic AI for the first time and how quickly they believe in it.What you’ll be doing from day oneRun technical discovery, design solutions, and lead POCs alongside Account Executives to close deals, then own onboarding to get customers to first value fast.Build and implement workflows within V7 Go; combining prompt engineering, data pipelines, and integrations to solve real customer problems across document processing and more.Act as the primary technical contact for accounts, handling complex challenges and spotting expansion opportunities as customers scale.Juggle up to 10 concurrent projects while feeding customer insights back to product and engineering.Who you areYou are a prototyper at heart with a gift of talking to customers, building relationships, and solving technical problems with repeatability.You have experience in delivering Large Language Model projects with customers, including LLM API integration, up-to-speed knowledge of foundation models, solutions design/architecture, integrating different cloud providers, prompt engineering, and/or measuring AI accuracy.You love coding with Python.You can develop and articulate an AI solution vision to technical and business stakeholders, with customers and partners to match the value proposition to business needs.V7 champions equality and inclusion because diverse teams build better products. Don't check every box? Apply anyway — we value what makes you unique and will support you through the process, just let our Talent team know how they can help.

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The Perception team at Zoox creates the "eyes and ears" of our self-driving robots. Navigating safely and efficiently in complex environments requires detecting, classifying, tracking, and understanding various attributes of surrounding objects—all in real-time and with exceptional accuracy. As an engineer in the Scene Understanding team, you will develop advanced Vision-Language-Action (VLA) models that perceive our vehicle's surroundings to identify hazards and make driving suggestions. You will utilize VLA models for detecting rare events and ensuring safe driving in these situations. You'll work with state-of-the-art machine learning models that operate in real-time on our robotaxi platform with minimal latency. Collaborating with world-class engineers and researchers across sensors, planning, and other teams, you'll have access to premium sensor data and cutting-edge infrastructure to validate your algorithms in real-world conditions.In this role, you will... Design and train Vision-Language-Action (VLA) solutions for robotaxis Lead end-to-end data strategy, including mining, auto-labeling, and dataset construction to power our ML flywheel Lead the full post-training stack for VLMs and VLAs, including Continual Pre-training (CPT) on domain-specific driving data, Supervised Fine-Tuning (SFT) for instruction following. Utilize our large-scale data pipelines and ML infrastructure to research, prototype, and deploy solutions that improve driving behavior Partner with cross-functional teams to integrate perception signals Qualifications MS or PhD in Computer Science or related field Background in deep learning solutions for VLM and VLA models Track record in post-training large-scale models, CPT, SFT, RL Hands-on experience with production ML pipelines, including dataset creation, training frameworks, and metrics Expertise in Python libraries (PyTorch, NumPy, Pandas, VLLM) Bonus Qualifications Deep knowledge of cutting-edge computer vision techniques Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA) Experience with integrating large language models to various tasks. 189,000 - 290,000 a year Base Salary Range   There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.   Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance. About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter. A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

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🚀 Build the next generation of Agentic AI with us Our platform combines conversation intelligence, multimodal understanding, and agentic AI systems to power both human agents and autonomous AI agents across the entire customer experience lifecycle. A core part of this vision is our investment in custom Small Language Models (SLMs)—purpose-built for CX workflows—paired with reinforcement learning systems that continuously improve decision-making in real-world environments. We’re looking for a Research Intern (Reinforcement Learning) to join us in shaping this future. What you’ll do   Design and build reinforcement learning environments that model real-world customer interaction workflows. Design RL agents that learn from these environments using real-world interaction data, rewards, and feedback loops Define reward models and feedback loops using real-world signals (outcomes and human feedback) Enable learning from production data by structuring interaction traces into training-ready datasets for offline and online learning Experiment with multi-agent systems and simulation frameworks for complex coordination and decision-making Collaborate with engineering and product teams to deploy, evaluate, and iterate on learning systems in production at scale.   What we’re looking for Currently pursuing (or recently completed) a degree in Computer Science, AI, Machine Learning, or related field Strong understanding of reinforcement learning fundamentals Familiarity with RL environments and training libraries such as Verl and Tinker Strong foundation in probability, maths, and optimization Passion for building real-world AI systems Nice to have Experience with RLHF, LLM/SLM fine-tuning, or model alignment Exposure to agent-based systems or multi-agent RL Prior research, projects, or publications in RL or applied ML Experience working with large-scale or production datasets   Why Level AI Work on production-grade Agentic AI systems used by leading enterprises Build alongside a team with deep expertise from Amazon, Google, and Meta Be part of a fast-growing Series C AI company. Direct exposure to 0→1 AI innovation in CX and decisioning systems

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7AI is seeking an AI-Native Product Builder to design and launch intelligent security products that help organizations proactively defend against evolving cyber threats. This role blends product thinking with hands-on engineering, enabling you to move from idea to production quickly using AI-first workflows.You’ll work at the intersection of cybersecurity, AI, and product innovation—building systems that detect, analyze, and respond to threats in real time. From early concept validation to production deployment, you’ll own the full lifecycle of new capabilities, collaborating closely with engineering, research, and go-to-market teams.The ideal candidate is deeply technical, AI-native in how they build, and energized by solving complex security problems in a fast-moving, high-ownership environment.What You’ll DoRapidly prototype and ship new security features using AI coding tools (e.g., Cursor, Copilot) and modern development workflows to explore product ideas and technical feasibility.Leverage internal data, threat intelligence, and market signals to identify high-impact opportunities and validate product direction.Build and scale features across cloud platforms, APIs, and security infrastructure using GenAI to accelerate development while maintaining high standards for reliability and security.Own product definition end-to-end—translating ambiguous problems into clear requirements and shipped solutions.Balance trade-offs across security effectiveness, performance, usability, and operational complexity.Partner cross-functionally with engineering, security researchers, and business stakeholders to deliver impactful outcomes.Identify opportunities to automate workflows across teams using agentic AI systems and internal tooling.Contribute to the evolution of next-generation AI-driven cybersecurity capabilities, including detection, response, and analysis systems.What We’re Looking ForBachelor’s degree or higher in a technical field (or equivalent experience).5+ years of experience in software engineering, product development, or a hybrid role, including building AI-powered applications.Strong hands-on experience with LLMs and AI coding tools for prototyping, analysis, and product development.Experience building systems that incorporate GenAI (e.g., LLM integrations, RAG pipelines, agentic workflows, evaluation frameworks).Proven ability to take products from concept to launch with a strong focus on user impact.Nice to HaveExperience building security or infrastructure products (e.g., detection systems, monitoring tools, or distributed services).A portfolio of projects demonstrating AI-native development and rapid prototyping.Experience instrumenting products with analytics and telemetry to drive decision-making.Familiarity with cloud infrastructure (e.g., AWS) and data visualization tools.

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About the TeamOpenAI’s Stargate Infrastructure team is building and operating the systems that power next-generation AI workloads at massive scale. This includes deploying and managing clusters, networks, and data center infrastructure across first-party and partner environments.As the scale and complexity of these systems grow, we are investing in agentic systems and intelligent automation to improve how infrastructure is deployed, operated, and debugged. This team focuses on applying AI-driven approaches to real-world infrastructure workflows—enabling faster execution, higher reliability, and scalable operations.About the RoleWe are seeking an IC Agentic Engineering Manager to lead the development and application of agent-based systems for infrastructure delivery and operations within Stargate.This is a player-coach role: you will contribute directly to system design and implementation while leading a small team. You will focus on applying agentic systems to infrastructure workflows such as deployment orchestration, system bring-up, issue triage, debugging, and capacity management.This role is not focused on building general-purpose agent platforms. Instead, it is centered on applying agentic systems to solve concrete infrastructure problems, working closely with hardware, networking, and cluster teams.Key ResponsibilitiesDesign and build agent-based systems to support infrastructure deployment and operationsIdentify high-impact opportunities to apply agents across workflows such as:cluster bring-up and deployment readinessincident triage and root cause analysissystem validation and health monitoringcapacity management and operational decision-makingLead a small team while contributing directly as an IC across system design, development, and integrationPartner with infrastructure, hardware, and networking teams to integrate agentic systems into production workflowsDevelop systems that leverage telemetry, logs, and system signals to enable closed-loop automationDefine evaluation frameworks to measure system effectiveness, reliability, and operational impactDrive iteration from prototype to production, ensuring robustness and scalabilityQualificationsStrong software engineering background in distributed systems, infrastructure, or platform engineeringExperience building production automation systems or data-driven operational toolingExperience applying AI, ML, or agent-based approaches to real-world systems or workflowsAbility to operate as a hands-on IC while leading a small teamExperience working cross-functionally with infrastructure, hardware, or systems teamsStrong problem-solving skills in complex, ambiguous environmentsPreferred SkillsExperience with LLM-based systems, agents, or autonomous workflowsBackground in infrastructure operations, SRE, or large-scale system deploymentExperience working on cluster bring-up, debugging, or data center infrastructure systemsFamiliarity with telemetry, monitoring systems, and observability pipelinesExperience building internal tools or platforms for engineering productivity and operationsAbout OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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  About the Company Armada is a full-stack edge infrastructure company delivering compute, connectivity, and sovereign AI/ML to some of the world’s most remote places. Named one of Fast Company's Most Innovative Companies, Armada’s solutions are deployed in over 60 countries globally for organizations ranging from energy to defense.    With over $200 million in funding, Armada is backed by top investors such as Microsoft (M12), Founders Fund, and has strategic partnerships including Starlink, Skydio, and NVIDIA. We are looking for the most brilliant minds in the world to join us.    Working at Armada means taking ownership, driving autonomy, and delivering impact. You’ll tackle challenges that haven’t been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada’s mission to bridge the digital divide for customers around the world.      About the role At Armada, we are unlocking the limitless potential of AI to transform operations and improve lives in some of the most remote locations on Earth. From the expansive mines of Australia to the oil fields of Northern Canada, and the coffee plantations of Colombia, Armada offers a unique opportunity to tackle exciting AI and ML challenges on a global scale. We are actively seeking passionate AI Engineers with hands-on expertise across a range of domains, including real-time computer vision, statistical machine learning, natural language processing, transformers, control and navigation, reinforcement learning, and large-scale distributed AI systems. Ideal candidates will possess strong skills in machine learning (ML), deep learning (DL), and real-time computer vision techniques. You will be responsible for building ML/DL models tailored to specific challenges, preparing datasets for testing, evaluating model performance, and deploying solutions in production environments. Familiarity with containerization, microservices architecture, and the ability to independently deploy ML models into production is essential. If you are a self-driven individual with a passion for cutting-edge AI, we want to hear from you. Armada offers an unparalleled opportunity to confront some of the most thrilling AI and ML challenges in the world. Join our dynamic AI Engineering team as we deliver disruptive edge-compute systems capable of autonomous learning, prediction, and adaptation using vast, real-time datasets. We are pioneers in developing high-performance computing solutions for self-driving cars, camera networks, robotics, drones, conversational agents, and real-time monitoring and diagnostic systems. Our vision is to empower AI systems to seamlessly and securely interact with the complexities and uncertainties of the real world, and our mission is to bridge the digital divide in the process.  Location. This role is office-based at our Bellevue, Washington office.  What You'll Do (Key Responsibilities) Translating business requirements into requirements for AI/ML models. Preparing data to train and evaluate AI/ML/DL models. Building AI/ML/DL models by applying state-of-the-art algorithms, especially transformers. In some cases, leverage existing algorithms from academic or industrial research. Testing, evaluating the AI/ML/DL models, benchmarking their quality, and publishing the models, data sets, and evaluations. Deploying the models in production by containerizing the models. Working with customers and internal employees to refine the quality of the models. Establishing continuous learning pipelines for models with online learning or transfer learning. Building and deploying containerized applications on the cloud or on-premise environments Required Qualifications BS or MS degree in computer science, computational. science/engineering, or related technical field (or equivalent experience). 3+ years of work-related experience in software development with good Python, Java, and/or C/C++ programming skills. Familiarity with containers, numeric libraries, modular software design. Hands-on expertise with traditional statistical machine learning techniques as well as deep-learning and natural language processing modeling. Expertise in supervised, unsupervised, and transfer learning techniques. Hands-on expertise in machine learning techniques and algorithms with a strong background in state-of-the-art DNN architectures (Transformers, CNN, R-CNN, RNN, BERT, GAN, autoencoders, etc.) and experience in developing or using major deep learning frameworks (e.g., PyTorch, Tensorflow, etc). Experience with solving and using machine learning for real-world problems. Preferred Experience and Skills Demonstrable experience in building, programming, and integrating software and hardware for autonomous or robotic systems. Proven experience producing computationally efficient software to meet real-time requirements. Background with container platforms such as Kubernetes. Strong analytical skills with a bias for action. Strong time-management and organization skills to thrive in a fast-paced, dynamic environment. Solid written and oral communications skills. Good teamwork and interpersonal skills. Compensation For U.S. Based candidates: To ensure fairness and transparency, the starting base salary range for this role for candidates in the U.S. are listed below, varying based on location experience, skills, and qualifications. In addition to base salary, this role will also be offered equity and subsidized benefits (details available upon request). Benefits Competitive base salary and equity Medical, dental, and vision (subsidized cost) Health savings accounts (HSA), flexible spending accounts (FSA), and dependent care FSAs (DCFSA) Retirement plan options, including 401(k) and Roth 401(k) Unlimited paid time off (PTO) 14 paid company holidays per year #LI-SM2 #LI-Onsite   Compensation$154,560—$193,200 USD  You're a Great Fit if You're A go-getter with a growth mindset. You're intellectually curious, have strong business acumen, and actively seek opportunities to build relevant skills and knowledge  A detail-oriented problem-solver. You can independently gather information, solve problems efficiently, and deliver results with a "get-it-done" attitude  Thrive in a fast-paced environment. You're energized by an entrepreneurial spirit, capable of working quickly, and excited to contribute to a growing company A collaborative team player. You focus on business success and are motivated by team accomplishment vs personal agenda  Highly organized and results-driven. Strong prioritization skills and a dedicated work ethic are essential for you    Equal Opportunity Statement At Armada, we are committed to fostering a work environment where everyone is given equal opportunities to thrive. As an equal opportunity employer, we strictly prohibit discrimination or harassment based on race, color, gender, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law. This policy applies to all employment decisions, including hiring, promotions, and compensation. Our hiring is guided by qualifications, merit, and the business needs at the time.   Unsolicited Resumes and Candidates Armada does not accept unsolicited resumes or candidate submissions from external agencies or recruiters. All candidates must apply directly through our careers page. Any resumes submitted by agencies without a prior signed agreement will be considered unsolicited and Armada will not be obligated to pay any fees.  

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  About the Company Armada is a full-stack edge infrastructure company delivering compute, connectivity, and sovereign AI/ML to some of the world’s most remote places. Named one of Fast Company's Most Innovative Companies, Armada’s solutions are deployed in over 60 countries globally for organizations ranging from energy to defense.    With over $200 million in funding, Armada is backed by top investors such as Microsoft (M12), Founders Fund, and has strategic partnerships including Starlink, Skydio, and NVIDIA. We are looking for the most brilliant minds in the world to join us.    Working at Armada means taking ownership, driving autonomy, and delivering impact. You’ll tackle challenges that haven’t been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada’s mission to bridge the digital divide for customers around the world.      About the role At Armada, we are unlocking the limitless potential of AI to transform operations and improve lives in some of the most remote locations on Earth. From the expansive mines of Australia to the oil fields of Northern Canada, and the coffee plantations of Colombia, Armada offers a unique opportunity to tackle exciting AI and ML challenges on a global scale. We are actively seeking passionate AI Engineers with hands-on expertise across a range of domains, including real-time computer vision, statistical machine learning, natural language processing, transformers, control and navigation, reinforcement learning, and large-scale distributed AI systems. Ideal candidates will possess strong skills in machine learning (ML), deep learning (DL), and real-time computer vision techniques. You will be responsible for building ML/DL models tailored to specific challenges, preparing datasets for testing, evaluating model performance, and deploying solutions in production environments. Familiarity with containerization, microservices architecture, and the ability to independently deploy ML models into production is essential. If you are a self-driven individual with a passion for cutting-edge AI, we want to hear from you. Armada offers an unparalleled opportunity to confront some of the most thrilling AI and ML challenges in the world. Join our dynamic AI Engineering team as we deliver disruptive edge-compute systems capable of autonomous learning, prediction, and adaptation using vast, real-time datasets. We are pioneers in developing high-performance computing solutions for self-driving cars, camera networks, robotics, drones, conversational agents, and real-time monitoring and diagnostic systems. Our vision is to empower AI systems to seamlessly and securely interact with the complexities and uncertainties of the real world, and our mission is to bridge the digital divide in the process.  Location. This role is office-based at our Bellevue, Washington office.  What You'll Do (Key Responsibilities) Translating business requirements into requirements for AI/ML models. Preparing data to train and evaluate AI/ML/DL models. Building AI/ML/DL models by applying state-of-the-art algorithms, especially transformers. In some cases, leverage existing algorithms from academic or industrial research. Testing, evaluating the AI/ML/DL models, benchmarking their quality, and publishing the models, data sets, and evaluations. Deploying the models in production by containerizing the models. Working with customers and internal employees to refine the quality of the models. Establishing continuous learning pipelines for models with online learning or transfer learning. Building and deploying containerized applications on the cloud or on-premise environments Required Qualifications BS or MS degree in computer science, computational. science/engineering, or related technical field (or equivalent experience). 3+ years of work-related experience in software development with good Python, Java, and/or C/C++ programming skills. Familiarity with containers, numeric libraries, modular software design. Hands-on expertise with traditional statistical machine learning techniques as well as deep-learning and natural language processing modeling. Expertise in supervised, unsupervised, and transfer learning techniques. Hands-on expertise in machine learning techniques and algorithms with a strong background in state-of-the-art DNN architectures (Transformers, CNN, R-CNN, RNN, BERT, GAN, autoencoders, etc.) and experience in developing or using major deep learning frameworks (e.g., PyTorch, Tensorflow, etc). Experience with solving and using machine learning for real-world problems. Preferred Experience and Skills Demonstrable experience in building, programming, and integrating software and hardware for autonomous or robotic systems. Proven experience producing computationally efficient software to meet real-time requirements. Background with container platforms such as Kubernetes. Strong analytical skills with a bias for action. Strong time-management and organization skills to thrive in a fast-paced, dynamic environment. Solid written and oral communications skills. Good teamwork and interpersonal skills. Compensation For U.S. Based candidates: To ensure fairness and transparency, the starting base salary range for this role for candidates in the U.S. are listed below, varying based on location experience, skills, and qualifications. In addition to base salary, this role will also be offered equity and subsidized benefits (details available upon request). Benefits Competitive base salary and equity Medical, dental, and vision (subsidized cost) Health savings accounts (HSA), flexible spending accounts (FSA), and dependent care FSAs (DCFSA) Retirement plan options, including 401(k) and Roth 401(k) Unlimited paid time off (PTO) 14 paid company holidays per year #LI-SM2 #LI-Onsite   Compensation$154,560—$193,200 USD  You're a Great Fit if You're A go-getter with a growth mindset. You're intellectually curious, have strong business acumen, and actively seek opportunities to build relevant skills and knowledge  A detail-oriented problem-solver. You can independently gather information, solve problems efficiently, and deliver results with a "get-it-done" attitude  Thrive in a fast-paced environment. You're energized by an entrepreneurial spirit, capable of working quickly, and excited to contribute to a growing company A collaborative team player. You focus on business success and are motivated by team accomplishment vs personal agenda  Highly organized and results-driven. Strong prioritization skills and a dedicated work ethic are essential for you    Equal Opportunity Statement At Armada, we are committed to fostering a work environment where everyone is given equal opportunities to thrive. As an equal opportunity employer, we strictly prohibit discrimination or harassment based on race, color, gender, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law. This policy applies to all employment decisions, including hiring, promotions, and compensation. Our hiring is guided by qualifications, merit, and the business needs at the time.   Unsolicited Resumes and Candidates Armada does not accept unsolicited resumes or candidate submissions from external agencies or recruiters. All candidates must apply directly through our careers page. Any resumes submitted by agencies without a prior signed agreement will be considered unsolicited and Armada will not be obligated to pay any fees.  

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About Liquid AISpun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.The OpportunityThis is a rare chance to apply frontier sequential recommendation architectures to real enterprise problems at scale. You will own applied ML work end-to-end for recommendation system workloads, adapting Liquid Foundation Models for customers who need personalization and ranking capabilities that run efficiently under production constraints.Unlike most recommendation roles that are siloed into a single product surface, this role gives you full ownership over how large-scale recommendation models are adapted, evaluated, and deployed for enterprise customers. Between engagements, you will build reusable applied tooling and workflows that accelerate future delivery.If you care about data quality at scale, user behavior modeling, and making recommendation systems actually work in enterprise production environments, this is the role.What We’re Looking ForWe need someone who:Takes ownership: Owns customer recommendation system engagements end-to-end, from requirements through delivery and evaluation.Thinks at scale: Can reason about user interaction data, sequential modeling, feature engineering, and evaluation across large-scale production systems.Is pragmatic: Optimizes for measurable customer outcomes (engagement, conversion, revenue lift) over theoretical novelty.Communicates clearly: Can translate between customer business metrics and internal technical decisions, and push back when needed.The WorkAct as the technical owner for enterprise customer engagements involving recommendation and ranking workloadsTranslate customer requirements into concrete specifications for recommendation modelsDesign and execute data pipelines for user interaction data, feature engineering, and training data curation at scaleFine-tune and adapt large-scale sequential recommendation models (e.g., HSTU-style architectures) for customer-specific use casesDesign task-specific evaluations for recommendation model performance (ranking quality, latency, throughput) and interpret resultsBuild reusable applied tooling and workflows that accelerate future customer engagementsDesired ExperienceMust-have:Hands-on experience building or fine-tuning recommendation models at scale (not just off-the-shelf collaborative filtering)Experience with sequential recommendation architectures, user behavior modeling, or large-scale ranking systemsStrong intuition for data quality and evaluation design in recommendation contexts (offline metrics, A/B testing, business metric alignment)Experience with large-scale data pipelines for user interaction data and feature engineeringProficiency in Python and PyTorch with autonomous coding and debugging abilityNice-to-have:Experience with transformer-based recommendation architectures (HSTU, SASRec, BERT4Rec, or similar)Experience delivering recommendation systems to external customers with measurable business outcomesFamiliarity with serving recommendation models under latency and throughput constraintsWhat Success Looks Like (Year One)Independently owns and delivers enterprise recommendation system engagements with minimal oversightIs trusted by customers as the technical owner, demonstrating strong judgment on the tradeoffs between model quality, latency, and business impactHas built reusable applied workflows or tooling that accelerate future customer engagementsWhat We OfferReal ML work: You will build and adapt large-scale recommendation models for enterprise customers, working with frontier architectures like HSTU under real production constraints.Compensation: Competitive base salary with equity in a unicorn-stage companyHealth: We pay 100% of medical, dental, and vision premiums for employees and dependentsFinancial: 401(k) matching up to 4% of base payTime Off: Unlimited PTO plus company-wide Refill Days throughout the year

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About Liquid AISpun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there. The OpportunityThis is a rare chance to sit at the intersection of frontier vision-language models and real-world deployment. You'll own applied post-training work for VLMs end-to-end for some of the world's largest enterprises, while still contributing directly to Liquid's core multimodal model development.Unlike most roles that force a trade-off between customer impact and foundational work, this role gives you both: deep ownership over how vision-language models are adapted, evaluated, and shipped, and a direct line into the evolution of Liquid's multimodal post-training stack.If you care about visual understanding, data quality, evaluation, and making VLMs actually work in production, this is a chance to shape how applied multimodal AI is done at a foundation model company. What We're Looking ForWe need someone who:Takes ownership: Owns VLM post-training projects end-to-end, from customer requirements through delivery and evaluation.Thinks end-to-end: Can reason across visual data curation, training, alignment, and evaluation as a single system.Is pragmatic: Optimizes for model quality and customer outcomes over publications or theory.Communicates clearly: Can translate between customer needs and internal technical teams, and push back when needed.The WorkAct as the technical owner for enterprise customer VLM post-training engagements.Translate customer requirements into concrete multimodal post-training specifications and workflows.Design and execute visual data generation, filtering, and quality assessment processes, including image-text pair curation, annotation pipelines, and synthetic data generation for visual tasks.Run supervised fine-tuning, preference alignment, and reinforcement learning workflows for vision-language models.Design task-specific evaluations for visual understanding, grounding, OCR, document parsing, and other multimodal capabilities. Interpret results and feed learnings back into core post-training pipelines.Desired ExperienceMust-have:Hands-on experience with data generation and evaluation for VLM or multimodal post-training.Experience training or fine-tuning vision-language models using SFT, preference alignment, and/or RL.Strong intuition for visual data quality, annotation design, and multimodal evaluation.Familiarity with vision encoders, image-text architectures, and how visual representations interact with language model backbones.Nice-to-have:Experience with visual grounding, document understanding, OCR, or video understanding tasks.Experience contributing to shared or general-purpose multimodal post-training infrastructure.Prior exposure to customer-facing or applied ML delivery environments.Familiarity with alignment or RL techniques beyond basic supervised fine-tuning in the multimodal setting.What Success Looks Like (Year One)Independently owns and delivers enterprise VLM post-training projects with minimal oversight.Is trusted by customers as the technical owner, demonstrating strong judgment and delivery quality on multimodal workloads.Has made durable contributions to Liquid's general-purpose multimodal post-training pipelines by feeding applied learnings back into baseline model development.What We OfferReal ML work: You will fine-tune vision-language models, generate multimodal data, and ship solutions, not configure API calls. Your work feeds directly back into our core model development.Compensation: Competitive base salary with equity in a unicorn-stage company.Health: We pay 100% of medical, dental, and vision premiums for employees and dependents.Financial: 401(k) matching up to 4% of base pay.Time Off: Unlimited PTO plus company-wide Refill Days throughout the year.

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About the roleTaktile is building a platform for creating, publishing, and executing AI-powered agents that help teams automate complex workflows in financial services. The Agents team owns the agent execution runtime, tool orchestration, and platform infrastructure that makes this possible.We are hiring a Back-End Engineer to help build and ship production features across this stack. You'll work alongside experienced engineers, contribute to real product impact from day one, and grow your skills in a fast-moving, high-ownership environment.Taktile is a hybrid company. This role requires working at least 3 days per week from our Berlin HQ.What You'll DoBuild and ship backend features for Taktile's AI agent platform in Python (FastAPI), deployed on AWS serverless infrastructure.Own your work end-to-end: collaborate on scope, implement, test, release, and iterate based on real usage and customer feedback.Improve how agents run, how they connect to external tools, and how they behave when something goes wrong.Use leading-edge AI tools (e.g. Claude) on a daily basis to move faster, improve quality, and build AI-native capabilities where it makes sense.Review pull requests with depth, improve test coverage and CI/CD, and raise the bar on reliability and engineering excellence.Engage actively in team rituals such as daily syncs, planning sessions, demos, and technical deep-dive discussions.Grow as an individual and accelerate your career by learning from experienced team members, contributing to a foundational layer of the product, and joining cross-team learning groups.For career growth at Taktile, this role will involve daytime ops duty and at some point joining an on-call rotation, so you need to have passion for owning systems end to end and grow your DevSecOps skills as well.Technical stackBackend: Python (FastAPI, Pydantic)Data: DynamoDB, PostgresCloud: AWS serverless (Lambda, API Gateway)AI: LLM orchestration, tool-use frameworks, streaming executionFrontend: React, TypeScript (you will collaborate closely, but this is not a front-end role)RequirementsStrong engineering fundamentals with a passion for simplicity and precision.Fluency in English, both written and spoken, is essential as we operate in a remote environment requiring clear and effective communication. Strong English skills are also crucial to efficiently interacting with AI.Prior industry experience with Python back-end development (this is not an entry-level position).Experience building and operating RESTful APIs and working with databases.Experience integrating into AWS or similar cloud providers.Ideally, but not requiredFastAPI and Pydantic experience.DynamoDB or Postgres, SQLAlchemy.Exposure to LLM application development, agent frameworks, or building developer tools.Prior ops or on-call experience.Experience with distributed systems, async task processing, or observability tooling (tracing, metrics, logging).Our OfferWork with colleagues that lift you up, challenge you, celebrate you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields. If you are similarly capable, caring, and driven, you'll find yourself at home here.Experience a truly flat hierarchy and communicate directly with founding team members. Having an opinion and voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo.Learn from experienced mentors and achieve tremendous personal and professional growth. Get to know and leverage our network of leading tech investors and advisors around the globe.Receive a top-of-market equity and cash compensation package.Get access to a self-development budget you can use to e.g. attend conferences, buy books or take classes.Receive a new Apple MacBook Pro, as well as meaningful home office set-up.Our StanceWe're eager to meet talented and driven candidates regardless of whether they tick all the boxes. We're looking for someone who will add to our culture, not just fit within it. We strongly encourage individuals from groups traditionally underestimated and underrepresented in tech to apply.We seek to actively recognize and combat racism, sexism, ableism and ageism. We embrace and support all gender identities and expressions, and celebrate love in its many forms. We won't inquire about how you identify or if you've experienced discrimination, but if you want to tell your story, we are all ears.About usTaktile helps financial institutions make smarter, safer decisions with the power of AI. Our software gives teams the tools to automate complex decisions like who to onboard, how to underwrite, or when to flag suspicious activity with full visibility and control.By combining AI with a rich ecosystem of financial data, Taktile enables companies to adapt their decision-making in real time as markets, customer behavior, and risks evolve.Our mission is to build the world's leading platform for automated decision-making in financial services, setting the standard for how AI is applied responsibly and effectively in this industry.We were founded by machine learning and data science experts with deep experience in financial services. Today, our team works across Berlin, London, and New York, bringing together engineers, entrepreneurs, and researchers from companies like Google, Amazon, and Meta, as well as fast-growing startups and enterprise leaders.Backed by top investors including Y Combinator, Index Ventures, Balderton Capital, and Tiger Global, along with the founders of Looker, GitHub, Mulesoft, Datadog, and UiPath, we're building a world-class organization across all functions and levels to power the next generation of AI-driven decision-making in financial services.

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About Liquid AISpun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.The OpportunityThis is a rare chance to own applied post-training work end-to-end for audio workloads, adapting Liquid Foundation Models for customers who need speech and audio capabilities that run on-device under real-time constraints.You will act as the technical bridge between customer requirements and model delivery for audio tasks. You will lead engagements from scoping through evaluation, with full ownership over how audio models are adapted and shipped. Between engagements, you will build reusable applied workflows and tooling that accelerate future delivery.If you care about audio data quality, speech model evaluation, and making audio models actually work in production for real customers, this is the role.What We’re Looking ForWe need someone who:Takes ownership: Owns customer post-training projects end-to-end for audio workloads, from requirements through delivery and evaluation.Thinks end-to-end: Can reason across audio data pipelines, speech-text alignment, model adaptation, and evaluation as a connected system.Is pragmatic: Optimizes for model quality and customer outcomes over publications or theory.Thrives under constraints: On-device, low-latency, memory-limited audio systems excite you. You see constraints as design parameters, not blockers.The WorkAct as the technical owner for enterprise customer post-training engagements involving audio and speech workloadsTranslate customer requirements into concrete post-training specifications for ASR, TTS, and speech-to-speech tasksDesign and execute data generation, preprocessing, augmentation, and quality filtering processes for audio corporaFine-tune and adapt audio/speech models for customer-specific use cases, owning delivery from requirements through deploymentDesign task-specific evaluations for audio model performance (noise robustness, speaker variation, latency) and interpret resultsBuild reusable applied tooling and workflows that accelerate future customer engagementsDesired ExperienceMust-have:Hands-on experience with data generation and evaluation for ML model post-trainingExperience training or fine-tuning models using SFT, preference alignment, and/or RLStrong intuition for data quality and evaluation designExperience with speech or audio ML models (ASR, TTS, audio understanding, vocoders, or speech-to-speech systems)Proficiency in Python and PyTorch with autonomous coding and debugging abilityNice-to-have:Experience with audio data pipelines at scale (preprocessing, augmentation, quality filtering)Experience delivering applied ML work to external customers with measurable outcomesFamiliarity with on-device deployment under latency and memory constraintsWhat Success Looks Like (Year One)Independently owns and delivers enterprise post-training projects for audio workloads with minimal oversightIs trusted by customers as the technical owner for audio engagements, demonstrating strong judgment and delivery qualityHas built reusable applied workflows or tooling that accelerate future customer engagementsWhat We OfferReal ML work: You will fine-tune audio and speech models, build audio data pipelines, and ship solutions to enterprise customers under real-time on-device constraints.Compensation: Competitive base salary with equity in a unicorn-stage companyHealth: We pay 100% of medical, dental, and vision premiums for employees and dependentsFinancial: 401(k) matching up to 4% of base payTime Off: Unlimited PTO plus company-wide Refill Days throughout the year