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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is seeking a ASIC Networking Engineer to help define and build next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications. You will contribute to our current datacenter networking efforts while also helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. The initial focus will be datacenter networking, with robotics as the first target within the automotive/robotics space. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are You thrive while navigating multiple priorities and ambiguous, evolving requirements. You have knowledge of Ethernet  network architecture and how performance is modeled. You have experience with die-to-die interfaces and understand associated protocols and design tradeoffs. You understand Ethernet networking concepts and how they map onto on-chip and off-chip fabrics. You have experience with datacenter scale up architectures like UALink, NVLink, and Broadcom SUE. You have experience with scale out RDMA protocols like RoCE, Infiniband, and others. Experience working on safety (diagnostic and fault coverage) with RTL design process.   What We Need A network ASIC designer who can contribute to both datacenter networking and early-stage automotive/robotics scoping and specifications. Someone comfortable working at the intersection of NoC, performance modeling, and RTL design to guide architectural decisions. An engineer who can collaborate across hardware, software, and systems teams to define and refine networking requirements. A contributor who can help drive forward next-generation CPU networking architecture for AI/ML workloads.   What You Will Learn How to build next-generation CPU networking architectures for both high-performance datacenter and constrained robotics/automotive environments. How to help drive forward next-generation robotics-focused CPUs for AI/ML compute with rich sensor ingestion. How to work at the intersection of NoC design, performance modeling, and RTL to close the loop between architecture and implementation. How to take an early-stage concept (automotive/robotics networking) from seeding and specification through to project initiation.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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About the RoleA1 is building a proactive AI system that carries work forward across conversations, tools, and time.You define what we build and why, grounded in what AI systems can actually do in production. You sit at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable user value.This is a hands-on role for product leaders who are comfortable making decisions under uncertainty and working closely with engineers on hard technical trade-offs.What You'll be DoingOwn the end-to-end AI product strategy, grounded in technical feasibility and real-world constraints.Translate model capabilities, data limitations, and evaluation results into clear product decisions.Make hard trade-offs across quality, latency, cost, reliability, and user experience.Work daily with ML, backend, and mobile engineers on design, evaluation, and iteration.Define success metrics and feedback loops across offline evaluation, online experiments, and human feedback.Drive execution with clear specifications, risk awareness, and disciplined prioritization.Ensure AI features ship quickly, safely, and reliably into production.Own AI product quality across UX, correctness, and outcomes.What You Will NeedTechnical foundationStrong grounding in computer science fundamentals, including algorithms, data structures, and system design.Solid understanding of ML fundamentals and how modern AI systems behave in production.Comfort reading, reviewing, and discussing technical design documents.AI & ML experienceHands-on exposure to AI-powered products, including LLM-based systems.Experience working with model evaluation, prompt or pipeline iteration, and feedback loops.Strong intuition for model limitations, hallucinations, bias, and drift.Product leadershipSignificant experience owning complex, technical products end-to-end.Proven ability to work closely with senior engineers and ML teams.Strong judgment and decision-making ability in ambiguous, fast-moving environments.Ability to balance ambition with technical and operational reality.Nice to haveExperience shipping AI-heavy consumer products.Background as an engineer or highly technical product manager.Experience defining evaluation metrics for ML systems.Strong intuition for AI UX patterns and failure handling.Prior experience in zero-to-one product environments.How We WorkOur organization is very flat and our team is small, highly motivated, and focused on engineering and product excellence. All members are expected to be hands-on and to contribute directly to the company’s mission.Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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About the RoleA1 is building a proactive AI system that carries work forward across conversations, tools, and time.You define what we build and why, grounded in what AI systems can actually do in production. You sit at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable user value.This is a hands-on role for product leaders who are comfortable making decisions under uncertainty and working closely with engineers on hard technical trade-offs.What You'll be DoingOwn the end-to-end AI product strategy, grounded in technical feasibility and real-world constraints.Translate model capabilities, data limitations, and evaluation results into clear product decisions.Make hard trade-offs across quality, latency, cost, reliability, and user experience.Work daily with ML, backend, and mobile engineers on design, evaluation, and iteration.Define success metrics and feedback loops across offline evaluation, online experiments, and human feedback.Drive execution with clear specifications, risk awareness, and disciplined prioritization.Ensure AI features ship quickly, safely, and reliably into production.Own AI product quality across UX, correctness, and outcomes.What You Will NeedTechnical foundationStrong grounding in computer science fundamentals, including algorithms, data structures, and system design.Solid understanding of ML fundamentals and how modern AI systems behave in production.Comfort reading, reviewing, and discussing technical design documents.AI & ML experienceHands-on exposure to AI-powered products, including LLM-based systems.Experience working with model evaluation, prompt or pipeline iteration, and feedback loops.Strong intuition for model limitations, hallucinations, bias, and drift.Product leadershipSignificant experience owning complex, technical products end-to-end.Proven ability to work closely with senior engineers and ML teams.Strong judgment and decision-making ability in ambiguous, fast-moving environments.Ability to balance ambition with technical and operational reality.Nice to haveExperience shipping AI-heavy consumer products.Background as an engineer or highly technical product manager.Experience defining evaluation metrics for ML systems.Strong intuition for AI UX patterns and failure handling.Prior experience in zero-to-one product environments.How We WorkOur organization is very flat and our team is small, highly motivated, and focused on engineering and product excellence. All members are expected to be hands-on and to contribute directly to the company’s mission.Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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About the roleMaincode is training Matilda, the first large language model built and trained from scratch in Australia. Our new compute cluster is live, and we are now scaling the next version.This role sits directly inside that training stack. You will build the pipelines, infrastructure, and tooling that determine how efficiently Matilda trains, how stable long runs are, and how fast new experiments can be executed. Training runs last days or weeks. Small changes propagate through complex systems. The work requires precision and patience.We build AI systems from first principles: designing the architectures, running the infrastructure, shaping the training process, and operating the models ourselves. Matilda is not a research prototype. It is a production system, trained at scale and served for open public access.Maincode operates one of the largest private AI compute environments in Australia, built for a single purpose: training our own models. This is not a role that wraps external APIs or ships user-facing features. You will be working on the systems that train a large language model from scratch.What you would actually doYou will build and maintain the systems that support large scale model training.This includes:Designing and maintaining distributed training pipelines for large language modelsBuilding data ingestion and preprocessing systems for large training datasetsDeveloping tooling for experiment management, checkpointing, and reproducibilityMonitoring and debugging long running training jobs across clustersImproving reliability and observability across the training stackOptimising training throughput across compute, memory, and data pipelinesWorking closely with researchers to translate experimental ideas into training runsDiagnosing failures across infrastructure, training loops, and data pipelinesTraining runs can last days or weeks. Small changes propagate through complex systems.You will spend time inside code, logs, dashboards, and experiment outputs. The goal is simple: make large scale training reliable.The kind of person who does well hereWe are looking for engineers early in their careers who want to understand how large models are actually trained.You may have one or two years of experience building production software. What matters most is curiosity and the willingness to learn how these systems behave under load.People who tend to do well here:Care about how systems behave over long runtimesEnjoy debugging complex distributed systemsPay attention to logs, metrics, and system behaviourPrefer understanding how a system works rather than relying on abstractionAre comfortable working close to infrastructureHave the patience to diagnose failures that appear hours into a runWant to learn how large scale AI training actually happensYou do not need prior experience training large language models. What matters is intellectual curiosity, persistence, and the ability to learn quickly.How you would workYou will write production code that sits directly in the training stack.You should be comfortable:Working in PythonUsing machine learning frameworks such as PyTorch or JAXWriting reliable infrastructure for large compute workloadsDebugging distributed systems and long running jobsCollaborating closely with researchers and infrastructure engineersMuch of the work sits between research and infrastructure. Ideas move quickly, but the systems that support them must remain stable.What this role is notIt is not primarily about building user facing applicationsIt is not about prompt engineeringIt is not about wrapping external APIs or third party modelsYou will be working on the systems that train our own models from scratch.Why MaincodeMaincode builds AI systems end to end. We prepare the data, design the training process, run the infrastructure, and operate the models ourselves.You will work with a small team that:Builds the full AI stack rather than outsourcing itTreats infrastructure as part of the intelligence system itselfValues engineers who want to understand how things actually workIs building long term capability in training and operating large modelsIf you want to work directly on the systems that train large language models from scratch, this is the only role in Australia that will put you inside that work.NoteThis is a full time role based in Melbourne, working closely with our in person engineering and research team. At this time we are not able to offer visa sponsorship, so applicants must have existing and unrestricted work rights in Australia.

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About the roleMaincode builds foundation models from first principles on Australian infrastructure. We design architectures, run our own compute, shape the training process, and operate the systems that serve our models.We have built Matilda, the first large language model built and trained from scratch in Australia. Our new compute cluster is live; we are scaling the next version of Matilda and deploying and serving it live for public access.We are looking for AI researchers who want to work on the core architecture, training, and evaluation of large-scale language models that power Matilda.This role is not focused on incremental benchmarking or paper output. You will work directly with the engineers running large-scale training systems and help design models that learn efficiently and behave reliably in production.What you would actually doYou will work across the model development loop, from research questions to training runs to evaluation.This includes:Designing and testing architecture changes and training regimes for large language modelsRunning controlled experiments at scale and isolating causal effectsStudying failure modes in reasoning, generalisation, robustness, and representationShaping objectives, data mixtures, and optimisation choices that influence model behaviourBuilding and refining evaluations that measure capability and reliability, not just scoresAnalysing training dynamics using logs, metrics, and model outputsCollaborating with ML systems engineers on distributed training and training operationsWriting clear internal notes that turn experimental results into design decisionsYou will spend substantial time in code, training runs, logs, and evaluation outputs. The goal is clarity about what improves the model and why.What we are looking forWe care about depth of reasoning, experimental discipline, and the ability to make progress under ambiguity.We expect:Hands-on experience writing and running production-grade ML or research codeStrong Python and experience with PyTorch or JAXSolid understanding of transformer-based language models and the basics of pre-training and evaluationAbility to design experiments, interpret results, and communicate tradeoffs clearlyComfort working close to infrastructure, performance constraints, and operational realityInterest and exposure to reasoning-oriented architectures and training methods beyond standard approaches, and beyond standard LLMs Nice to haveExperience with distributed training concepts and tooling (data parallel, tensor parallel, sharding, checkpointing)Experience running training across multiple nodes and managing long training cyclesFamiliarity with large-model training stacks and frameworks (for example Megatron-style systems, DeepSpeed-like tooling, or equivalent)Comfort across the full workflow: training, evaluation, and deployment constraintsExperience working in ROCm-based environmentsHow you would workThis is hands-on research. You will use code as a primary tool for thinking.You will be expected to:Move between theory and implementation quickly and preciselyPrefer controlled experiments over broad sweepsUse logs, metrics, and model behaviour to guide decisionsWork closely with engineering counterparts to scale and validate ideasWhat this role is notIt is not a product research roleIt is not prompt engineeringIt is not fine-tuning someone else’s model and shipping wrappers around external APIsYou will work on Matilda, trained from scratch on our infrastructure, and pushed until its behaviour is understood and improved.Why MaincodeMaincode builds and operates the full stack: training infrastructure, model code, evaluation systems, and deployment. We run one of the largest private AI compute environments in Australia, built for the sole purpose of training and deploying large scale models.If you want to work directly on training and evaluating a large language model built from scratch, this is the only role in Australia that will put you inside that work.NoteThis is a full time role based in Melbourne, working closely with our in person team. At this time we are not able to offer visa sponsorship, so applicants must have existing and unrestricted work rights in Australia.

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Our Mission:At Sunrise Robotics, we are dedicated to augmenting humanity through intelligent robotics. Our mission is to elevate the world of manufacturing by introducing intelligent, flexible robots that enhance human capabilities and existing machinery, ushering in the next era of production at higher quality, with less waste, and lower cost. Our Vision:We see a future where every element of manufacturing, from design to assembly, is optimised with intelligent automation. Our vision is to integrate flexible robotic solutions, based on generic hardware and advanced software/AI capabilities, into manufacturing, particularly in small and medium-sized enterprises, to make automation economically viable and accessible, for all sizes of manufacturers. We are not just building robots; we are creating the strategically crucial components for autonomous, intelligent agents of the future.The role:Sunrise Robotics is building a new category of intelligent, flexible robotic automation - designed to scale across factories, not just solve one-off integrations. As a Forward Deploy Engineer, you’ll be at the front lines of that transformation.This is a unique role that sits between product and deployment. You’ll work directly with customers to deliver automation solutions in real production environments, while continuously improving how those solutions are packaged, standardised, and scaled. The challenge is not simply delivering systems - it’s helping turn delivery into a repeatable, efficient, productised capability.You’ll bring practical experience from traditional automation or system integration and apply it to a new model: scalable deployment powered by Sunrise tools, products, and processes. Your work will directly shape how we refine our offering for customers and our roadmap for product teams to reduce non-recurring engineering effort and speed market adoption.What you’ll do:Deploy Sunrise robotic systems in live manufacturing environments, ensuring successful customer go-livesTranslate real-world production constraints into structured feedback that improves product capabilities and deployment workflowsIdentify opportunities to reduce non-recurring engineering effort and improve delivery scalabilityContribute to the refinement of Sunrise’s tools, processes, and system architecture to enable repeatable deploymentsCollaborate closely with AI, robotics, product, and commercial teams to align customer needs with product evolutionSupport pilot launches and early deployments, ensuring systems meet defined performance and operational success criteriaAct as a technical partner to customers during integration, building trust and ensuring long-term successProvide technical support to customers during troubleshooting and maintenance of deployed robotic systemsInvestigate and respond to operational incidents or anomalies in robotic systems, ensuring timely resolution and system reliabilityWhat you’ll need:A genuine drive to reinvent how flexible automation solutions are delivered and scaled across manufacturing environmentsHands-on experience deploying robotic systems and automated machinery in real-world industrial settingsStrong understanding of robotics fundamentals and familiarity with deep learning models, including how they can be adapted or re-trained for specific applicationsWorking knowledge of synthetic data generation concepts, simulation environments such as NVIDIA Isaac Sim / Omniverse, and structured quality assurance processesExperience with ROS 2 and Behaviour Tree programming for robotic system controlAn abstract, systems-level thinker who can view problems from multiple perspectives and generalise solutions across different applicationsAbility to collaborate effectively with multidisciplinary teams across AI, mechanical, electrical, and software engineeringStrong communication skills, able to explain complex technical concepts clearly to both technical and non-technical stakeholdersA deep passion for robotics, automation, and building intelligent systems that transform manufacturingWhat Makes You Stand Out:Experience in collaborative applications.Experience with ABB SafeMove.Experience with TIA portal.Experience with radar-based safety.Experience with safety analysis tools.Why Us?We’re building a new category of intelligent, flexible robotic automation with real deployments, real customers, and momentum across Europe.Why this role: You’ll operate at the intersection of product and deployment, helping transform automation delivery from bespoke integration to scalable, repeatable systems.Career acceleration: High ownership, deep cross-functional exposure, and the opportunity to shape how a category-defining robotics company scales globally.Real impact: Your work won’t stay in simulation or design reviews - it will run on real factory floors, directly influencing product evolution, customer success, and company trajectory.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!About North:North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.Why This Role?This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We are seeking engineers with diverse skill sets, including backend, infrastructure, agent development, and deployments, who deeply care about customers and want to work at the cutting edge of Agentic AI.Note: between 20 - 40% travel anticipatedIn this role, you will:Build and ship features for North, our AI workspace platformDevelop autonomous agents that talk to sensitive enterprise dataExperiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectationsWork across the entire product lifecycle from conceptualization through productionLead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rolloutYou may be a good fit if:You have experience with and enjoy working directly with customersYou are fluent in both English and ArabicYou have shipped (lots of) Python in productionYou have built and deployed highly performant client-side or server-side RAG/agentic applicationsYou have strong coding abilities and are comfortable working across the stack. You’re able to read and understand, and even fix issues outside of the main code baseYou excel in fast-paced environments and can execute while priorities and objectives are a moving targetWe are open to candidates currently based in the Middle East or who are open to travelling or relocating.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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About AbridgeAbridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. The RoleWe are looking for passionate GenAI Engineers of all levels who are passionate about making a positive impact. You’ll collaborate closely with a cross-functional team of researchers, clinicians, and engineers to translate cutting-edge language model capabilities into dependable, real-world clinical systems. Your focus will be on designing advanced LLM-driven workflows that can reason through complex clinical contexts, leverage agentic capabilities and structured tool use, navigate branching chains of LLM calls, integrate seamlessly with retrieval systems, and consistently generate outputs that meet the highest standards of clinical reliability and trust.A major part of this role will involve developing and applying rigorous evaluation frameworks (both automated and human-in-the-loop) to continuously assess accuracy, robustness, multilingual capabilities, and more. This is an opportunity to design experiments to probe failure modes, simulate edge cases, and stress-test LLM workflows under realistic load and challenging real-world conditions. You’ll apply a disciplined, data-driven approach to understanding model behavior—developing tools to measure system performance, conduct A/B tests against established baselines, and generate clear, actionable insights that inform deployment decisions. This high impact role will own the end-to-end productionization of LLM workflows: deploying models into low-latency, high-uptime environments, building monitoring and observability systems, implementing post-processing guardrails, and managing workflow versioning.What You’ll DoDesign and build GenAI systems that turn LLMs into composable, dependable tools—leveraging retrieval, tool use, agentic reasoning, and structured outputs.Collaborate with ML and infra engineers to scale and optimize GenAI workflows, managing latency, context windows, and model choice.Write high-quality, modular code that’s graceful under failure, flexible to change, and easy to iterate on.Own major architectural decisions—how we architect workflows,define data flow, cache intermediate state, and structure generative outputs.Drive rigorous evaluation: build benchmark datasets, develop automated and human-in-the-loop frameworks, design experiments to surface failure modes and edge cases, run A/B tests to inform deployment, and distill insights from clinician feedback to evaluate and guide model improvement.Leverage frontier capabilities: rapidly prototype with new models and model capabilities, open-source tools, and novel prompting techniques.What You’ll Bring3+ years of experience building production-grade systems, with 1–2+ years focused on GenAI or LLM-powered products.Deep fluency with LLM APIs, prompting strategies, and orchestration patterns (e.g., LangChain, LlamaIndex, custom pipelines).Experience with retrieval systems (e.g., semantic and lexical retrieval, vector DBs, efficient kNN), function calling, tool-use, or agentic workflows.Working knowledge of model evaluation, experience building diverse datasets, conducting both automated and human-in-the-loop evaluations, running A/B tests, and working with subject matter experts to guide model improvement.Strong Python fundamentals—including ability to write clean code, design comprehensive test-cases, and familiarity with core language features and standard libraries; experience with async programming, performance profiling, packaging, and deployment tooling is strongly preferred.Good taste and intuition: You know when to move fast, ship, and iterate and also when to take a beat to tackle tech debt.We value people who are eager to learn new things and recognize that great team members might not perfectly match a job description. If you’re interested in the role but aren’t sure whether or not you’re a good fit, we’d still like to hear from you.Must be willing to work from our SF office at least 3x per weekThis position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of (3) three times per week. Relocation assistance is available for candidates willing to move to San Francisco.Why Work at Abridge?At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. How we take care of Abridgers:Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employeesComprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.Paid Parental Leave: Generous paid parental leave for all full-time employees.Family Forming Benefits: Resources and financial support to help you build your family.401(k) Matching: Contribution matching to help invest in your future.Personal Device Allowance: Tax free funds for personal device usage.Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.Compensation and Equity: Competitive compensation and equity grants for full time employees.... and much more!Equal Opportunity EmployerAbridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.Staying safe - Protect yourself from recruitment fraudWe are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions. 

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About the TeamTraining Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI.Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability.Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs.About the RoleAs a Training Runtime: Process Management Engineer, you will work on the software that ties thousands of computers together and exposes them as a unified system.This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout.You will work primarily in Rust, building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability.Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure.We’re looking for people who love optimizing an end-to-end platform, understanding high-performance architectures to maximize both local and distributed performance across our supercomputers. We’re looking for engineers excited by the rapid pace of responding to the dynamic and evolving needs of our training runtime and compute stack.This role is based in London, UK. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.In this role, you will:Work across our Python and Rust stackDesign, build, and maintain software to orchestrate and monitor machine learning workloads on our largest supercomputersProfile and optimize our software stack to support computation orchestration at frontier scaleImprove reliability, observability, and fault tolerance for long-running jobsDebug complex distributed systems issues across large clustersRespond to the changing shapes and needs of the ML systems to enable our researchers You might thrive in this role if you:Have experience developing distributed systems (not just operating them)Enjoy understanding how large systems behave and fail at scaleCare deeply about performance, correctness, and reliabilityHave strong software engineering skills and are proficient in Python and Rust or another systems programming language (e.g. C++)Have solid Linux knowledge, and are comfortable with systems-level debugging, performance analysis, and memory profilingAre comfortable and experienced working and developing asynchronous and concurrent systemsLike high-ownership environments with light process and strong engineering agencyAbout OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamThe Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework.Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.The mission of the Preparedness team is to:Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our societyEnsure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systemsPreparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society.About the RoleAs a threat modeler, you will own OpenAI’s holistic approach to identifying, modeling, and forecasting frontier risks from frontier AI systems. This role ensures that our evaluation frameworks, safeguards, and taxonomies are robust, high-coverage, and forward-looking. You will help the company answer the “why” behind our most stringent risk-prevention efforts, shaping the rationale for prioritizing and mitigating risks across domains. You will serve as a central node connecting technical, governance, and policy perspectives on prioritization, focus and rationale on our approach to frontier risks from AI.In this role, you will:Develop and maintain comprehensive threat models across all misuse areas (bio, cyber, attack planning, etc.).Develop plausible and convincing threat models across loss of control, self-improvement, and other possible alignment risks from frontier AI systemsForecast risks by combining technical foresight, adversarial simulation, and emerging trends.Pair closely with technical partners on capability evaluations to ensure these map to and cover the gambit of severe risks differentially enabled by frontier AI systems.Pair closely with Bio and Cyber Leads to size the remaining risk of the designed safeguards and translate threat models into actionable mitigation designs.Act as the thought partner and explainer of “why” and “when” for high-investment mitigation efforts—helping stakeholders understand the rationale behind prioritization.Serve as the central node connecting technical, governance, and policy perspectives on prioritization, focus and rationale on our approach to misuse risk.You might thrive in this role if you:Understand risks from frontier AI systems and have a strong grasp of AI alignment literature. Bring deep experience in threat modeling, risk analysis, or adversarial thinking (e.g., security, national security, or safety).Know how AI evaluations work and can connect eval results to both capability testing and safeguard sufficiency.Enjoy working across technical and policy domains to drive rigorous, multidisciplinary risk assessments.Communicate complex risks clearly and compellingly to both technical and non-technical audiences.Think in systems and naturally anticipate second-order and cascading risks.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About Us:Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B at a $1.1B valuation. Our investors include Lux Capital, Redpoint Ventures, Amplify Partners, and Elad Gil.Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. Our team includes creators of popular open-source projects (e.g. Seaborn, Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.The Role:We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own.The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will:Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads on ModalContribute to open-source projects — members of the team are active contributors to SGLang — and publish technical content that demonstrates Modal's capabilities across the AI stackCollaborate with Modal's product and sales teams, contributing to the platform as both an engineer and a product stakeholderBuild trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI workConduct technical demos, experiments, and proof-of-concepts that make Modal's performance advantages tangibleRequirements:2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructureFamiliarity with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains. You don't need all of these, but you should be able to go deep on at least one.Strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadershipGenuine interest in working directly with customers — you find it energizing to understand someone else's problem and help them solve itBonus: side projects, open-source contributions, or published work you're proud of in ML or systems performanceWilling to work in-person in Stockholm

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About GranicaGranica is an AI research and infrastructure company focused on reliable, steerable representations for enterprise data.We earn trust through Crunch, a policy-driven health layer that keeps large tabular datasets efficient, reliable, and reversible. On this foundation, we’re building Large Tabular Models—systems that learn cross-column and relational structure to deliver trustworthy answers and automation with built-in provenance and governance.Research Product Manager — Structured AI Systems & Economic ExtractionLocation: Downtown Mountain View, CA (office-based, five days a week) Team: Research & Applied SystemsThe MissionGranica’s Research team is advancing foundational work in:Tabular data learning and large tabular modelsStructured and relational representation learningCompression-aware and efficiency-driven AIHybrid symbolic, relational, and neural systemsThe intersection of information theory, learning theory, and large-scale systemsThese efforts are tightly coupled with real production systems operating over petabytes of enterprise data.The mission of the Research Product Manager is to ensure this work moves forward coherently, efficiently, and at scale—connecting people, ideas, compute, and systems so that breakthrough research becomes durable capability.This role is not program management.It is for someone who can:Understand how large AI models are trained, deployed, and maintained in production systemsTranslate foundational modeling advances into economically valuable infrastructureShape both the technical execution path and the economic strategy behind itWhat This Role Actually Owns1️⃣ Productionization of Structured AI ModelsWork with Research and Systems teams to:Design how large tabular models are trained on Parquet / Iceberg / Delta dataDefine training infra requirements (data pipelines, distributed training, evaluation loops)Define inference architecture (batch vs streaming, embedding materialization, retrieval)Define maintenance loops (retraining cadence, data drift detection, schema evolution)Understand storage/compute trade-offs in real systemsYou must be able to reason about:Data layoutCompute schedulingModel lifecycleInfrastructure bottlenecksEvaluation pipelines2️⃣ Economic Value ExtractionHelp define:Who the buyer is (infra teams, ML teams, data platform teams)Where economic value is unlocked (compression, compute savings, model accuracy, governance)How value is quantified (cost curves, workload modeling, infra substitution)How to convert research capability into revenue and durable platform advantageThis role requires strong intuition around enterprise infra economics.3️⃣ Research → Durable SystemYou will:Identify which modeling advances are worth productionizingKill research directions that lack economic or system viabilityDefine integration paths into enterprise workloadsWork directly with the Chief Research Scientist on research agenda prioritizationRequired BackgroundYou must have experience in at least one of:A) Production AI SystemsImplementing or PM’ing deployment of large models in productionTraining infra / inference infra / model maintenanceOperating over structured datasets (Parquet, columnar storage, data lakes)B) Economic Platform ThinkingDefining buyer, pricing, ROI, and cost structure of AI infrastructureConverting modeling advantage into business valueIdeally both.This Role Is NOTA coordination-heavy research program managerA consumer AI personalization PMA pure academic researcherCore QualificationsBackground in computer science, AI, mathematics, physics, engineering, or a closely related field.Comfort engaging deeply with researchers and engineers on complex technical topics.Strong SignalsExperience working with or within a research lab (academic or industrial).Familiarity with modern AI research workflows, including experimentation, evaluation, and large-scale training.Ability to abstract at a high level while also diving into details when needed.Strong written and verbal communication, especially around technical progress and trade-offs.Bonus ExperienceMaster’s or PhD in a relevant technical field.Publications or direct contributions to AI research (e.g., modeling, data, evals, systems, or related areas).Experience supporting research in structured data, tabular models, or system-aware ML.Demonstrated ability to learn new technical domains quickly.Why This Role MattersGranica is building foundational technology with a long horizon. The research happening here—particularly in structured and tabular AI—is aimed at reshaping how intelligence is built and applied across the global economy.As a Research Product Manager, you will:Enable breakthrough research to happen faster and land harder.Help define how frontier ideas become real systems.Play a central role in shaping the execution engine behind a generational research agenda.This role has real ownership, real influence, and a deep connection to the core of the company. Location & Work ModelThis role is office-based in Downtown Mountain View, five days a week. We believe close, in-person collaboration is essential for the kind of deep, cross-disciplinary research and execution this role requires. Why GranicaFundamental Research Meets Enterprise Impact. Work at the intersection of science and engineering, turning foundational research into deployed systems serving enterprise workloads at exabyte scale.AI by Design. Build the infrastructure that defines how efficiently the world can create and apply intelligence.Real Ownership. Design primitives that will underpin the next decade of AI infrastructure.High-Trust Environment. Deep technical work, minimal bureaucracy, shared mission.Enduring Horizon. Backed by NEA, Bain Capital, and various luminaries from tech and business. We are building a generational company for decades, not quarters or a product cycle.Compensation & BenefitsCompetitive salary, meaningful equity, and substantial bonus for top performersFlexible time off plus comprehensive health coverage for you and your familySupport for research, publication, and deep technical explorationAt Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring. Join us to build the foundational data systems that power the future of enterprise AI!

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Our MissionAleph Alpha is one of the few companies in Europe with end-to-end in-house model development including pre- and post-training. We’re building models that have general-purpose capabilities, but also specifically excel at addressing the needs of our customers.We're growing our post-training team in Heidelberg (or hybrid in Germany) and are looking for an AI Researcher who combines a deep theoretical understanding of reinforcement learning methods with a desire to improve on the state of the art and improve model capabilities in large-scale training.Team CultureAt Aleph Alpha, we foster a culture built on ownership, autonomy, and empowerment. Teams and individual contributors are trusted to take responsibility for their work and drive meaningful impact. We maintain a flat organizational structure with efficient, supportive management that enables quick decision‑making, open communication, and a strong sense of shared purpose.About the role As a (senior) AI Researcher for reinforcement learning you will shape and improve the underlying RL methodology, maintain a high-quality training code-base, and conduct large-scale experiments to hill-climb our performance benchmarks. This role is for you if you both have a strong theoretical background on RL and the engineering drive to bring these methods into production and improve on the methods as part of the reinforcement learning team.In your day-to-day you will conduct large-scale reinforcement learning experiments, derive hypotheses from the results, and iterate on both the implementation and methodology based on the observations. Together with a collaborative team, you will have direct impact on the models that we ship to our customers.This role is for Aleph Alpha Research GmbH.Your ResponsibilitiesHill-climb in large-scale training: Conduct large-scale LLM training runs, analyze evaluation scores in depth, propose hypotheses for improvement and directly implement them in order to maximize performance on our benchmarks.Theoretical innovation: Stay at the bleeding edge of RL research. You will identify, implement, and iterate on novel approaches to multi-turn reinforcement learning.Scale our training infrastructure: Identify bottlenecks in our training setup and optimize our RL training loops for large-scale training.Cross-functional collaboration: Partner with our other post-training teams to turn raw feedback into actionable training signals, ensuring that our RL iterations lead to measurable improvements in downstream performance.Your ProfileBasic QualificationsA deep understanding of Reinforcement Learning theory and how it relates to modern RL methods.Experience with multi-node LLM training (ideally using RL). You understand how to scale multi-node RL trainings and can reason about and implement distributed algorithms.Familiarity with statistical methods for evaluation and experiment design.Ability to reason about what an evaluation/environment measures and whether it matters - not just run benchmarks, but understand them.Strong Python skills and comfort with ML tooling (especially torch distributed)Willingness to relocate to Heidelberg or travel regularly (potentially weekly).Preferred QualificationsPhD in reinforcement learning or equivalent research experience.A history of contributions to top-tier venues (NeurIPS, ICML, ICLR, etc.) specifically regarding RL.Experience evaluating LLM models and crafting environments for training.Compensation and BenefitsBecome part of an AI revolution!30 days of paid vacationAccess to a variety of fitness & wellness offerings via WellhubMental health support through nilo.healthSubstantially subsidized company pension plan for your future securitySubsidized Germany-wide transportation ticketBudget for additional technical equipmentFlexible working hours for better work-life balance and hybrid working modelVirtual Stock Option PlanJobRad® Bike Lease

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About AbridgeAbridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. The RoleAbridge is hiring Research Scientists to join our Strategic Research team to rigorously evaluate and advance the real-world impact of ambient AI on patient outcomes, care quality, and provider experience. In this role, you will design and lead empirical studies of Abridge models and products in partnership with health systems, leveraging large-scale clinical conversation data to generate new insights about care delivery, documentation quality, clinical decision-making, and downstream patient outcomes. You will operationalize complex constructs—such as quality of care, safety, cognitive burden, and return on investment—using principled measurement frameworks and rigorous experimental or quasi-experimental methods. Working closely with our science and product teams, you will also develop evaluation frameworks that inform model development and product strategy. Your work will contribute to broader scientific understanding of how AI systems affect patients and providers in the real world. This role sits at the intersection of methodological innovation and practical impact, applying serious measurement science to systems that directly shape patient care.About Strategic Research: The Strategic Research team at Abridge has two primary functions: (i) designing and conducting rigorous research studies investigating the impact of ambient AI as an intervention in partnership with collaborating health systems; and (ii) supporting external research efforts that leverage Abridge data. In addition to driving and supporting empirical studies of the impact of ambient AI-enabled technologies, the team works closely with our science and engineering teams on core model evaluation. The common thread to all our work is ensuring that every partner-facing research initiative meets the highest standards of rigour, credibility, and strategic value.What You’ll DoDesign and conduct evaluations of Abridge models and productsEngage with external researchers and other stakeholders on designing and conducting research on ambient AI and research that leverages Abridge dataDevelop a strong user-centric and patient-centric mindset, grounding the research in empathy for the real world experience of providers and patientsCollaborate across our cross-functional product teams to ensure the research is deeply informed by current practices and our product roadmapWrite technical reports and give presentations to internal and external stakeholdersActively contribute to the wider research community by publishing original research in leading peer-reviewed publication venuesMentor research internsWhat You’ll BringPhD in statistics, biostatistics, computer science, economics, information systems, clinical informatics, or a related field.Expertise in rigorous quantitative or mixed-methods approaches for conducting evaluations using observational and experimental data.Strong research track record in evaluation and measurement, as evidenced by high-impact publications at peer-reviewed journals or conferences.A problem-before-method mindset. You do not change the question to make it amenable to simple analysis, but instead push the methodological frontier to solve the real world problems that matter to health systems, providers, and patients.A curious, adaptable, and proactive mindset, with a desire to learn and grow as a researcher in a fast-paced startup environment.Passion for and understanding of Abridge’s mission.Must be willing to work from our New York City office at least 3x per week.This position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of (3) three times per week. Relocation assistance is available for candidates willing to move to New York City.We value people who want to learn new things, and we know that great team members might not perfectly match a job description. If you’re interested in the role but aren’t sure whether or not you’re a good fit, we’d still like to hear from you.Why Work at Abridge?At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. How we take care of Abridgers:Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employeesComprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.Paid Parental Leave: Generous paid parental leave for all full-time employees.Family Forming Benefits: Resources and financial support to help you build your family.401(k) Matching: Contribution matching to help invest in your future.Personal Device Allowance: Tax free funds for personal device usage.Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.Compensation and Equity: Competitive compensation and equity grants for full time employees.... and much more!Equal Opportunity EmployerAbridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.Staying safe - Protect yourself from recruitment fraudWe are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions. 

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is seeking a ASIC Networking Engineer to help define and build next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications. You will contribute to our current datacenter networking efforts while also helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. The initial focus will be datacenter networking, with robotics as the first target within the automotive/robotics space. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are You thrive while navigating multiple priorities and ambiguous, evolving requirements. You have knowledge of Ethernet  network architecture and how performance is modeled. You have experience with die-to-die interfaces and understand associated protocols and design tradeoffs. You understand Ethernet networking concepts and how they map onto on-chip and off-chip fabrics. You have experience with datacenter scale up architectures like UALink, NVLink, and Broadcom SUE. You have experience with scale out RDMA protocols like RoCE, Infiniband, and others. Experience working on safety (diagnostic and fault coverage) with RTL design process.   What We Need A network ASIC designer who can contribute to both datacenter networking and early-stage automotive/robotics scoping and specifications. Someone comfortable working at the intersection of NoC, performance modeling, and RTL design to guide architectural decisions. An engineer who can collaborate across hardware, software, and systems teams to define and refine networking requirements. A contributor who can help drive forward next-generation CPU networking architecture for AI/ML workloads.   What You Will Learn How to build next-generation CPU networking architectures for both high-performance datacenter and constrained robotics/automotive environments. How to help drive forward next-generation robotics-focused CPUs for AI/ML compute with rich sensor ingestion. How to work at the intersection of NoC design, performance modeling, and RTL to close the loop between architecture and implementation. How to take an early-stage concept (automotive/robotics networking) from seeding and specification through to project initiation.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is seeking a ASIC Networking Engineer to help define and build next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications. You will contribute to our current datacenter networking efforts while also helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. The initial focus will be datacenter networking, with robotics as the first target within the automotive/robotics space. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are You thrive while navigating multiple priorities and ambiguous, evolving requirements. You have knowledge of Ethernet  network architecture and how performance is modeled. You have experience with die-to-die interfaces and understand associated protocols and design tradeoffs. You understand Ethernet networking concepts and how they map onto on-chip and off-chip fabrics. You have experience with datacenter scale up architectures like UALink, NVLink, and Broadcom SUE. You have experience with scale out RDMA protocols like RoCE, Infiniband, and others. Experience working on safety (diagnostic and fault coverage) with RTL design process.   What We Need A network ASIC designer who can contribute to both datacenter networking and early-stage automotive/robotics scoping and specifications. Someone comfortable working at the intersection of NoC, performance modeling, and RTL design to guide architectural decisions. An engineer who can collaborate across hardware, software, and systems teams to define and refine networking requirements. A contributor who can help drive forward next-generation CPU networking architecture for AI/ML workloads.   What You Will Learn How to build next-generation CPU networking architectures for both high-performance datacenter and constrained robotics/automotive environments. How to help drive forward next-generation robotics-focused CPUs for AI/ML compute with rich sensor ingestion. How to work at the intersection of NoC design, performance modeling, and RTL to close the loop between architecture and implementation. How to take an early-stage concept (automotive/robotics networking) from seeding and specification through to project initiation.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system. Responsibilities Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems Bonus Qualifications Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.) The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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About the TeamOpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.About the RoleYou will develop and evolve the tooling ecosystem that hardware engineers rely on every day — from hardware compilers and IR transformations to simulation, debugging, and automation infrastructure. The work spans software engineering, compiler concepts, and practical hardware workflows, with direct impact on how quickly and effectively we design next-generation AI systems.You’ll collaborate closely with architects, RTL designers, and verification engineers to translate real engineering friction into durable, scalable tooling solutions.In this role you will:Build and improve the software tooling that makes hardware teams faster: compilation, IR transforms, RTL generation, simulation, debug, and automation.Extend and integrate hardware compiler stacks (frontends, IR passes, lowering, scheduling, codegen to Verilog/SystemVerilog) and connect them to real design workflows.Improve developer experience and reliability: reproducible builds, better error messages, faster iteration loops, and dependable CI and regression infrastructure.Work closely with designers and verification engineers to turn real pain points into durable tools.Dive into RTL when needed: read and reason about Verilog/SystemVerilog to debug issues, validate tool output, and improve debuggability.Be willing to go all the way down the stack when necessary, including gate-level views, synthesis results, and implementation artifacts.Help enable PPA optimization loops by building analysis and automation around area, timing, and power tradeoffs, and by improving tooling that impacts those outcomes.You might thrive in this role if:Demonstrated ability to build and maintain software (projects, internships, research, open source, or equivalent experience).Strong CS fundamentals: data structures, algorithms, debugging, and software design.Proficiency in at least one of Rust, C++, or Python (and willingness to learn the rest).Familiarity with digital design concepts and the ability to read RTL (Verilog/SystemVerilog) or equivalent hardware descriptions.Familiarity with compiler or IR-based ideas (representations, passes, transformations, lowering), through coursework or projects.Comfort operating in ambiguity and iterating quickly with users of your tools.Nice to have skills:Exposure to compiler and hardware toolchains such as XLS/DSLX, LLVM, Chisel/FIRRTL, CIRCT/MLIR, other novel hardware languages (e.g. HardCaml, SpinalHDL, Spade, PyMTL, Clash, BlueSpec, PyRope)Experience with Verilog tooling ecosystems (Yosys/RTLIL, Verilator, Slang) or writing tooling around them.Experience with build and test infrastructure (Bazel, CI systems, fuzzing, performance testing).Prior work touching synthesis, place and route, static timing analysis, or other PPA-related workflows.To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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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 on 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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Who are Heidi?Heidi is building an AI Care Partner that supports clinicians every step of the way, from documentation to delivery of care.We exist to double healthcare’s capacity while keeping care deeply human. In 18 months, Heidi has returned more than 18 million hours to clinicians and supported over 73 million patient visits. Today, more than two million patient visits each week are powered by Heidi across 116 countries and over 110 languages.Founded by clinicians, Heidi brings together clinicians, engineers, designers, scientists, creatives, and mathematicians, working with a shared purpose: to strengthen the human connection at the heart of healthcare.Backed by nearly $100 million in total funding, Heidi is expanding across the USA, UK, Canada, and Europe, partnering with major health systems including the NHS, Beth Israel Lahey Health, MaineGeneral, and Monash Health, among others.We move quickly where it matters and stay grounded in what’s proven, shaping healthcare’s next era. Ready for the challenge?The RoleWorking closely with the Product Lead, you will be a Mid-level or Senior Fullstack Engineer who operates at the intersection of core product development and clinical application.This role requires formal medical training and real clinical experience. Your clinical background will directly inform how we design, evaluate, and ship AI features that support real-world care delivery. Experience working on clinical AI products is highly valued, as you’ll be shaping systems that must perform safely in production environments.What you’ll do:Build end-to-end AI features: Architect and ship fullstack solutions (from React frontends to Python backend services) that leverage our voice AI and LLMs to automate clinical workflows.Operationalize Voice AI: Implement and fine-tune audio processing pipelines, ensuring our Automatic Speech Recognition (ASR) and LLM agents perform accurately in diverse, real-world medical environments.Bridge the gap between model and product: Translate complex feedback from clinicians into technical solutions, rapidly prototyping and deploying improvements to model behavior, prompting strategies, and audio handling.Optimise for real-time interaction: Tune fullstack performance to handle real-time audio streaming and token generation, minimizing latency so clinicians have a seamless conversational experience.Partner with implementation and clinical teams: Shorten the feedback loop by shipping critical integrations and feature requests from concept to production in days, not quarters.What we will look for:Mastery of Fullstack fundamentals: You are equally proficient in Python and modern frontend frameworks (React/TypeScript), capable of owning a feature from the database schema to the UI interaction.Applied AI & Voice fluency: You have a working knowledge of LLM integration (RAG, prompt engineering) and audio technologies (ASR, speech processing) and know how to build around their probabilistic nature.Pragmatic problem solving: You balance engineering purity with the need for speed; you know when to build a robust system and when to ship a tactical solution to unblock a customer.Cloud fluency (AWS or GCP): You can spin up your own infrastructure (containers, serverless functions) and manage CI/CD pipelines to get your code into the hands of users independently.Rigorous testing in production: You understand that "works on my machine" isn't enough; you implement observability and feedback loops to monitor how your AI features perform in the wild.Medical degree with clinical experience, and ideally experience working on clinical AI products What do we believe in?Heidi builds for the future of healthcare, not just the next quarter, and our goals are ambitious because the world’s health demands it. We believe in progress built through precision, pace, and ownership.Live Forever - Every release moves care forward: measured, safe, and built to last. Data guides us, but patients define the truth that matters.Practice Ownership - Decisions follow logic and proof, not hierarchy. Exceptional care demands exceptional standards in our work, our thinking, and our character.Small Cuts Heal Faster - Stability earns trust, speed delivers impact. Progress is about learning fast without breaking what people depend on.Make others better - Feedback is direct, kindness is constant, and excellence lifts everyone. Our success is measured by collective growth, not individual output.Our mission is clear: expand the world’s capacity to care, and do it without losing the humanity that makes care worth delivering.Why you should Join HeidiReal product momentum. We’re not trying to generate interest, we’re channeling it. This is a rare chance to create a global impact as you immerse yourself in Australia’s fastest growing start-up.Equity from day one. When Heidi wins, you win. You’ll share directly in the success you help create.Unmatched impact. Play a pivotal role at a critical growth moment - all while working on a product that delivers tangible value to clinicians and patients every day.Work alongside world-class talent. Join a team of operators and builders who’ve scaled unicorns.Global reach. Help shape our international expansion as we bring Heidi to key international markets.Growth and balance. Enjoy a personal development budget, dedicated wellness days, subsidised gym membership, and your birthday off to recharge.Flexibility that works. A hybrid environment, with 3 days in the office.Heidi’s commitment to Diversity, Equity and InclusionHeidi is dedicated to creating an equitable, inclusive, and supportive work environment that brings people together from diverse backgrounds, experiences, and perspectives. Our strength is in our differences. We're proud to be an equal opportunity employer and are proud to welcome all applicants as we're committed to promoting a culture of opportunity for all.Help us reimagine primary care and change the face of healthcare in Australia and then around the world.