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Senior Robotics Research Engineer
We are a well-funded startup on a mission to build the nervous system for AI-powered robots in industrial applications. Founded by leading robotics researchers, we are growing our dynamic, world-class team to deploy robots at scale. Join us in helping people handle more throughout the supply chain! We are seeking a Senior Robotics Research Engineer to design and develop fundamental new contributions to core robotics libraries and runtime application software for Ambi products, focused on new technology for the future. You will work closely with the Software team and the CTO. In this role you will: Independently develop robot applications and capabilities (controls, planning, perception) Lead R&D projects for new AI-driven robot skills, powered by foundation models Contribute to AmbiOS core libraries in areas such as: (a) scalable AI training, algorithms, models, and evaluation, (b) perception modules, (c) image and point cloud processing, (d) motion planning policies, (e) collision checkers Support software deployments to AI-powered robotic systems in production with global brands Modify existing software and configurations for new customers You are a good fit if you have: Eagerness to learn, solve challenging problems, and lead with curiosity A desire for career growth, ownership of your work, and making an impact Excitement about amplifying human potential with state-of-the-art robotics Proficiency in C++, Python, Linux, Git, and, Docker Expertise in motion planning, contact physics, machine learning, and computer vision Experience in the following areas: robotics (3D rigid geometry, kinematics, motion planning), software architecture, state machines, multi-processing, operating systems (must know UNIX), drivers (cameras, sensors, other equipment), and software update systems An MS with four years of experience in commercial robotics software development or equivalent or PhD in a very related subject (BONUS) Experience in Rust In addition to competitive compensation, we offer benefits such as: Health, dental, and vision insurance 401k with 5% matching by Ambi Equity ownership Unlimited PTO Partial WFH Free parking on site at HQ Access to a full gym at HQ Free lunches 2x per week PLEASE NOTE: All applications must be submitted online for equitable review. We do not accept or review submissions sent via email, including to individual team members or engineers. This policy ensures a fair and streamlined process for everyone. FOR RECRUITERS: This position is direct-hire only; unsolicited resumes from recruiters will not be considered and may result in a fee waiver.
AI Algorithm Tech Lead
About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role This is a role in Aidoc’s core AI group, which specializes in developing cutting-edge AI solutions in healthcare, enhancing medical imaging and diagnostics. As a Tech Leader in the AI Algorithm Engineering group, you will play a pivotal role in both managing end-to-end AI research and development efforts and hands-on involvement in key-initiatives. Your responsibility will include design, implementation, guidance and mentoring for team members, and representing the AI considerations in cross-team discussions. You will leverage your extensive experience to lead multiple AI projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations. Responsibilities - Lead the design, development, and implementation of accurate and robust AI algorithms for medical data with a hands-on approach. - Collaborate with cross-functional teams, including data scientists, software engineers, product managers and clinical data experts, to ensure AI considerations have a profound impact on R&D and Product decisions across the projects. - Design and conduct research and experimentation to improve algorithm performance and accuracy. - Stay at the forefront of the latest advancements in AI and machine learning, particularly in the medical domain, and drive their adoption within the team. - Oversee multiple projects, ensuring successful execution, timely delivery and alignment with product and business objectives. - Provide strategic direction and technical mentoring to elevate the capabilities of the AI team. Requirements - Master's or Ph.D. degree in Computer Science, Electrical Engineering, Physics, or a related field. - 7+ years of experience in designing and implementing AI/DL algorithms, with a preference for experience in healthcare or medical imaging. - Proven track record of leading AI projects and delivering AI solutions to commercial success. - Exceptional analytical and problem-solving skills. - Strong ability to work independently and as part of a cross-functional team. - Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to non-technical stakeholders. - Proficiency in Python and familiarity with relevant AI/ML frameworks. - Experience in both computer vision and NLP is highly desirable. - Prior experience in the healthcare industry is an advantage. Working at Aidoc Our Perks: - Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) - We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. - Amazing and healthy breakfasts and lunches prepared daily by our personal chef! - Stocked up kitchen & meal card - Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. - Amazing culture - collaborative, transparent & fun! - Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.
Senior Product Counsel
ABOUT ABRIDGE Abridge 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 ROLE As an Senior Product Counsel (Data Products, Machine Learning, and AI), you'll play a pivotal role as the go-to legal advisor for the teams building Abridge's AI and machine learning models, products, and technologies. This role is highly cross-functional across Abridge with a focus on advising product teams on the cutting edge of AI model and product developments, from ambient clinical documentation to emerging agentic and multimodal healthcare experiences. This is a unique opportunity to work at the forefront of the legal, AI, and healthcare fields, shaping how a category-defining company navigates novel legal terrain. WHAT YOU'LL DO - Serve as go-to counsel and partner for teams building Abridge's core AI models and products, advising on legal issues that span model development, agentic workflows, multimodal outputs, and downstream clinical use. - Identify, address, and design practical mitigations for AI-specific legal risks, including model behavior, output accuracy, IP, data provenance and training rights, and liability for AI-generated content. - Develop and scale flexible legal processes, frameworks, and contract language suited to the pace of frontier AI development, rather than relying solely on precedent from other industries. - Serve as an internal expert on AI legal and policy matters, helping shape Abridge's positions on emerging AI regulation and representing those positions with external counsel, regulators, and industry groups as needed. - Support privacy impact assessments, model risk assessments, and data governance frameworks specific to AI training, fine-tuning, and deployment. - Partner with legal, product, and compliance stakeholders on AI principles such as transparency, accountability, and human oversight. WHAT YOU'LL BRING - Passion for Abridge's mission and the drive to support fast-moving AI product and research teams. - 8+ years of legal experience, including 4+ years counseling on AI, machine learning, or other emerging technology products. Prior in-house experience is required. - Creativity in navigating novel legal matters, including building new processes, language, and frameworks to meet the needs of a fast-moving company in an emerging industry. - Working knowledge of AI-specific legal issues, including IP and copyright in AI-generated content, training data rights, model liability, and responsible AI principles. - Proven ability to translate complex regulatory and technical AI concepts into clear, practical guidance for non-legal, technical audiences. - Comfort operating with ambiguity, tight timelines, and a high volume of novel legal questions with no settled precedent. - Strong sense of ownership, intellectual curiosity about technology, and sound judgment in ambiguous situations. BONUS POINTS IF… - You have prior in-house experience at a growth-stage AI or healthcare technology company. - You have a strong understanding of federal and state healthcare laws, including HIPAA and data privacy regulations, as applied to AI systems. This role is in San Francisco or New York City. Monday/Wednesday/Friday are in office days. 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 employees - Comprehensive 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 EMPLOYER Abridge 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. We're committed to providing reasonable accommodations throughout the interview process. Once you submit your application, we'll follow up with details on how to request an accommodation for interviewing, completing any assessments, or otherwise participating in the selection process. STAYING SAFE - PROTECT YOURSELF FROM RECRUITMENT FRAUD We 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 http://abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article https://consumer.ftc.gov/consumer-alerts/2023/05/scammers-are-hijacking-job-ads-heres-how-spot-fakes. Please exercise caution and cease communications if something feels suspicious about your interactions.
Member of Technical Staff, Intern (Spring 2027)
ABOUT ABRIDGE Abridge 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 ROLE We're looking for Software Engineering Interns to join Abridge's Engineering team for a 3-month internship program in Spring 2027, with the possibility of extension. You'll collaborate with our engineering team to build and ship real-world features that translate cutting-edge language model capabilities into dependable clinical systems. With mentorship and guidance, you'll gain hands-on experience designing, coding, and releasing AI-powered software that makes a meaningful impact on clinicians' workflows. What You'll Do - Design and build end-to-end features, enhancing our existing systems and contributing to agentic LLM workflows (retrieval pipelines, structured tool use, chained LLM calls) - Fix user-facing bugs and issues, and make quality-of-life improvements across our backend and frontend systems - Get hands-on with evaluation frameworks that measure accuracy, robustness, and clinical reliability - Help prototype with new models, prompting techniques, and open-source orchestration tools (LangChain, LlamaIndex, etc.) - Develop a strong user-centric mindset, building empathy for Abridge's clinicians and the challenges they face - Collaborate across cross-functional product teams — design, product, machine learning, and infrastructure — to ship features to our customers - Receive guidance from an experienced software engineering mentor, and collaborate one-on-one with teammates within your pod What You'll Bring - Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field - A strong interest in pursuing a full-time software engineering role in 2027 — high-performing interns are eligible to receive a return offer - AI tooling is already part of how you work — you use it to write, debug, and learn faster, and you know when to trust it vs. verify - Passion for and understanding of Abridge's mission - A curious, adaptable, and proactive mindset, with a desire to learn and grow in a fast-paced startup environment - A collaborative, low-ego mindset — we move fast, and we need team players who are eager to contribute wherever needed Base Salary: $40/hr Must be willing to work from our San Francisco (Potrero) office 5x per week. This internship is based in our San Francisco office. Relocation to SF will be supported through reimbursements. 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 employees - Comprehensive 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 EMPLOYER Abridge 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. We're committed to providing reasonable accommodations throughout the interview process. Once you submit your application, we'll follow up with details on how to request an accommodation for interviewing, completing any assessments, or otherwise participating in the selection process. STAYING SAFE - PROTECT YOURSELF FROM RECRUITMENT FRAUD We 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 http://abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article https://consumer.ftc.gov/consumer-alerts/2023/05/scammers-are-hijacking-job-ads-heres-how-spot-fakes. Please exercise caution and cease communications if something feels suspicious about your interactions.
Member of Technical Staff, Intern (Fall 2026)
ABOUT ABRIDGE Abridge 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 ROLE We're looking for Software Engineering Interns to join Abridge's Engineering team for a 3-month internship program in Fall 2026, with the possibility of extension. You'll collaborate with our engineering team to build and ship real-world features that translate cutting-edge language model capabilities into dependable clinical systems. With mentorship and guidance, you'll gain hands-on experience designing, coding, and releasing AI-powered software that makes a meaningful impact on clinicians' workflows. What You'll Do - Design and build end-to-end features, enhancing our existing systems and contributing to agentic LLM workflows (retrieval pipelines, structured tool use, chained LLM calls) - Fix user-facing bugs and issues, and make quality-of-life improvements across our backend and frontend systems - Get hands-on with evaluation frameworks that measure accuracy, robustness, and clinical reliability - Help prototype with new models, prompting techniques, and open-source orchestration tools (LangChain, LlamaIndex, etc.) - Develop a strong user-centric mindset, building empathy for Abridge's clinicians and the challenges they face - Collaborate across cross-functional product teams — design, product, machine learning, and infrastructure — to ship features to our customers - Receive guidance from an experienced software engineering mentor, and collaborate one-on-one with teammates within your pod What You'll Bring - Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field - A strong interest in pursuing a full-time software engineering role in 2027 — high-performing interns are eligible to receive a return offer - AI tooling is already part of how you work — you use it to write, debug, and learn faster, and you know when to trust it vs. verify - Passion for and understanding of Abridge's mission - A curious, adaptable, and proactive mindset, with a desire to learn and grow in a fast-paced startup environment - A collaborative, low-ego mindset — we move fast, and we need team players who are eager to contribute wherever needed Base Salary: $40/hr Must be willing to work from our San Francisco (Potrero) office 5x per week. This internship is based in our San Francisco office. Relocation will be supported through reimbursements. 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 employees - Comprehensive 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 EMPLOYER Abridge 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. We're committed to providing reasonable accommodations throughout the interview process. Once you submit your application, we'll follow up with details on how to request an accommodation for interviewing, completing any assessments, or otherwise participating in the selection process. STAYING SAFE - PROTECT YOURSELF FROM RECRUITMENT FRAUD We 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 http://abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article https://consumer.ftc.gov/consumer-alerts/2023/05/scammers-are-hijacking-job-ads-heres-how-spot-fakes. Please exercise caution and cease communications if something feels suspicious about your interactions.
Senior to Staff AI Product Engineer
ABOUT 1X We’re building humanoid robots that work in the home – doing the chores, handling the tasks, and giving people their time back. Simple, but it’s not. To do this right, we have to solve robotics, AI, manufacturing – at the same time, at scale, in a form factor that has to be safe enough to live with your family. If you’re inspired by this, you’ll thrive here. NEO is our flagship - a home robot designed to move, learn, and operate in the real world alongside real people. We’re not demoing it - we’re shipping it! If you’ve spent your career working on problems that matter and want to see them actually reach the world - this is that moment. We’re scaling, we’re hiring with intention, and we need people who want to build something that will genuinely change how humans spend their time. ABOUT THE TEAM The Behavior team builds the software that enables NEO to be an intelligent, autonomous character living alongside people. We develop the decision-making systems, world simulation, and behavior frameworks that allow robots to perceive their surroundings, understand context, prioritize goals, and interact naturally in dynamic environments. YOUR CHARTER Build the behavior systems that bring humanoid robots to life. You will design scalable AI architectures that enable robots to reason about their environment, make autonomous decisions, manage competing goals, and perform complex tasks in real-world homes. You will build the systems that orchestrate multiple ML models with varying capabilities. Your work will create robots that behave naturally and reliably in real world situations. KEY OUTCOMES - Build an orchestration framework that interfaces with multiple LLMs, breaking complex tasks into simple steps. This will form the foundation for scalable behavior architectures that enable robots to autonomously perform household tasks naturally and intuitively. - Build systems that extract, store and index relevant details about environments and people. - Build decision-making frameworks using behavior trees, hierarchical state machines, or similar AI architectures. - Partner with Core, World Model, Apps, and Motion teams to integrate behavior systems into real-world robot operation. - Improve the realism, robustness, and adaptability of robot behaviors while establishing engineering best practices for large-scale behavior development. KEY COMPETENCIES - Expertise building products that leverage the capabilities of LLMs and custom ML models, exposing these in unique and intuitive user experiences. - Experience with multiple key AI technologies, such as conversational interfaces, agent orchestration, prompt engineering, MCPs, and management of agent context and memory. - Strong understanding of decision-making architectures, planning systems, and autonomous agent behaviors. - Excellent software engineering skills. - Strong systems thinking with the ability to simplify complex autonomous behaviors into maintainable software architectures. - Comfortable leading technical initiatives and collaborating across multidisciplinary engineering teams in a fast-moving environment. MINIMUM REQUIREMENTS - 6+ years of professional experience (Senior) or 10+ years (Staff) developing conversational AI, NPC behaviors, or system architecture. - Bachelor's degree in Computer Science, Software Engineering, Robotics, AI, or a related technical field. - System programming, and software design. PREFERRED SKILLS - Experience implementing behavior trees, GOAP, hierarchical state machines, planners, or similar AI architectures under tight performance constraints. - Experience building open-world games, large-scale simulations, conversational AI, or emergent gameplay systems. - Familiarity with robotics, autonomous systems, reinforcement learning, or embodied AI. - Experience with navigation systems, pathfinding, task scheduling, perception systems, or world modeling. - Experience developing tools that enable designers, researchers, or engineers to rapidly author and debug complex AI behaviors. WHAT DOES A SUCCESSFUL 1X TEAM MEMBER LOOK LIKE: Team members at 1X who thrive here are builders. They move fast, own their work completely, and treat time like it’s the one thing you can’t get back - because it is. They say what they mean, finish what they start, and hold themselves to a standard before anyone has to ask. We push each other to be better, and we do it with honesty and respect. COMPENSATION RANGE 190,000 – $280,000 + Equity BENEFITS - Comprehensive medical, dental, and vision coverage - Generous paid time off, company holidays, and parental leave - 401(k) plan with company match (100% on the first 3% of contributions, 50% on the next 2%) - Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA) options - Commuter benefits (transit and parking) - Short-term and long-term disability, and life insurance - Employee Assistance Program (EAP) for mental health, financial, and personal support - Onsite snacks and catered lunches EQUAL OPPORTUNITY EMPLOYER 1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, justice system impact, or any other characteristic protected under applicable federal, state, or local law.
AI Scientist, Computational Protein Design
About Xaira Therapeutics Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London. About the Role As an AI Scientist, you will have prior experience in developing and implementing new deep learning methods while upholding a track record of AI Innovation demonstrated through publications in Artificial Intelligence/Machine Learning or projects applying them to interdisciplinary fields. You will be a crucial member of our core AI team, comprising highly creative and talented peers who are all experts in developing state of the art AI models. With your team, you will initiate and drive new projects that advance the SOTA AI models for biology impacting drug discovery and clinical development. You will also have the chance to work closely with interdisciplinary experts with world-class biology, drug discovery, and clinical expertise. We welcome candidates with diverse backgrounds and experiences. Whether you are an entry-level candidate eager to learn and grow, a mid-level professional seeking new challenges, or a seasoned expert looking to make a significant impact, we encourage you to apply. Qualifications - Track record of AI Innovation demonstrated through publications in Artificial Intelligence/Machine Learning or projects applying them to interdisciplinary fields - Experienced in developing and implementing new deep learning methods - Experienced in PyTorch, training and inference of large models on GPUs - Scientifically curious with an interest to work on interdisciplinary teams - PhD in Computer Science/Artificial Intelligence/ Machine Learning or related technical fields - 3+ years of work experience post-PhD in an industrial setting or equivalent academic post-doctoral experience - Peer reviewed published research in developing AI methods (example in ICLR, NeurIPS, ICML, Nature, Science, Cell etc.) - Experience in working at the interface of AI and Biology - Experience working on large scale distributed training and inference - Experience communicating research for public audiences of peers - Participation in the open-source community Compensation We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $198,000 - $308,000 annually with a total cash compensation up to $228,000 - $362,000; however, the compensation offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience. Xaira Therapeutics is an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end. TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.
AI in Residence
About Xaira Therapeutics Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London. AI in Residence AI in Residence is a highly selective role at the intersection of frontier machine learning and drug discovery. Designed as an industry alternative to a traditional postdoctoral position, the program is for exceptional researchers and engineers who want to apply advanced AI to real biomedical problems end to end, from data to deployed systems. Residents join a small cohort working on high-impact AI efforts across Xaira. You’ll collaborate closely with AI scientists, research engineers, and drug discovery teams to design, build, and ship machine learning capabilities that directly influence therapeutic programs. This is hands-on, system-level work with real scientific consequence. We’re looking for candidates with technical depth, intellectual independence, strong research judgment, and evidence of delivering high-quality work—whether through publications, open-source, or production systems. What You’ll Do - Develop and advance ML models for biological, preclinical, and translational datasets (e.g., multimodal omics, imaging, text, assay data) - Design and implement scalable pipelines for data curation, training, evaluation, and inference integrated into discovery workflows - Own projects end-to-end: problem framing → prototyping → validation → deployment - Evaluate robustness and reliability (generalization, uncertainty, failure modes), plus interpretability where it supports scientific decision-making - Contribute technical leadership by proposing new directions, shaping platform capabilities, and raising engineering/research standards through collaboration You Might Work On Examples include (not limited to): - Foundation / representation models over multimodal biological and translational data - Methods for small, biased, noisy datasets; distribution shift; and uncertainty estimation - ML systems for experimental prioritization, assay interpretation, or translational signal discovery - Evaluation frameworks and benchmarks tailored to discovery decision-making - Tooling that makes models usable by scientists (interfaces, automation, monitoring) What Success Looks Like - You ship one or more models or pipelines that are used in real discovery workflows - Your work improves decision quality (e.g., better prioritization, faster iteration, clearer uncertainty) - You raise the bar on evaluation rigor and reproducibility (strong baselines, error analysis, reliable metrics) - You leave behind maintainable systems (tests, documentation, monitoring) that others can build on We Value - Strong research judgment: choosing the right problems and knowing what “good evidence” looks like - Rigor: careful experimental design, ablations, error analysis, and honest reporting - Systems thinking: reliability, scalability, and maintainability—not just prototypes Clear communication: writing, documentation, and sharing decisions/assumptions - Collaborative execution with scientific and engineering partners Program Structure Duration 6–12 months Start Dates Currently accepting applications for Fall 2026 and Winter/Spring 2027 starts. Cohort Size Small, highly selective cohort to enable meaningful ownership and close collaboration Mentorship & Support Dedicated technical mentor, plus structured feedback from senior AI, engineering, and scientific leadership Publications & Presentations We value scientific contribution and may support publications and conference presentations when appropriate. Publication scope and timing depend on project needs and are subject to internal review (e.g., IP and confidentiality). Authorship follows standard contribution-based guidelines. The Company consents to Employee completing, publishing, and maintaining the manuscript and repositories listed on Exhibit A, including bona fide revisions during peer review, provided such work is performed on Employee's own time and equipment, uses no Company resources or Proprietary Information, and does not relate to the Company's business or actual or anticipated research and development. This consent extends only to rights held by Employee and does not address or affect any rights of third parties. Who Should Apply We encourage applications from candidates who meet most of the following: - Recent MS or PhD graduates (or equivalent research experience) in ML/AI, computational biology, biomedical engineering, or related fields - Evidence of research excellence through high-quality publications or artifacts. Top venues (e.g., NeurIPS, ICML, ICLR, CVPR, ACL; Nature Methods, Cell Systems) are a plus, but strong preprints, open-source contributions, or shipped systems with demonstrated impact are equally compelling - Demonstrated ability to lead substantial technical work with originality—new modeling ideas, rigorous experiments, or production-grade systems adopted by others - Motivation to translate rigorous research into reliable, deployable AI systems that support therapeutic discovery Please include a brief cover letter describing your interest in this role, why you’re excited about this area, and what you hope to gain from the experience. Compensation: The expected monthly compensation range is $10,000–$15,000, depending on experience and qualifications. We are open to higher compensation for candidates with exceptional experience or impact.
Software quality engineer (UK)
🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role Are you passionate about ensuring the highest quality for cutting-edge generative AI applications? As a software quality engineer at WRITER, you'll play a critical role in shaping the reliability, performance, and trustworthiness of our AI-powered work orchestration platform. You’ll be at the forefront of defining and implementing rigorous quality strategies for our enterprise-grade LLMs and AI agents, directly impacting how hundreds of global companies unlock transformational value through AI. This is a unique chance to dive deep into the unique challenges of AI quality assurance and make a tangible difference in a rapidly evolving field. This is a hybrid role based out of our London, San Francisco, Seattle, and New York City hubs. You will report directly to the director of engineering. 🦸🏻♀️ What you'll do - Define and implement comprehensive quality assurance strategies and test plans for our AI agents and LLM-powered applications, ensuring exceptional product reliability and performance. - Designing and developing automation frameworks: creating robust, scalable, and maintainable automated test frameworks from scratch or enhancing existing ones. You’ll need proficiency in at least one language like Typsecript, Python. - Collaborate closely with product managers, machine learning engineers, and data scientists to understand complex AI features and model behaviors, translating them into effective test cases and validation criteria. - Drive the continuous improvement of our testing processes and infrastructure, integrating automated checks within our CI/CD pipelines to ensure rapid, high-quality releases. - Identify, document, and track software defects and inconsistencies, performing root cause analysis to provide actionable feedback to development teams. - Monitor production systems and AI model performance, proactively identifying potential issues and contributing to post-release quality validation. - Champion quality best practices across engineering teams, fostering a culture of ownership and continuous improvement in delivering world-class AI solutions. - Designing, managing, and maintaining test data strategies and mock services to ensure stable, isolated, and repeatable test execution. - Experience designing, developing, or integrating agentic AI systems, AI skills, and the Model Context Protocol (MCP). - Manage the full defect lifecycle by analyzing customer feedback and debugging logs to identify, prioritize, and track software bugs, collaborating closely with development teams to ensure timely resolution. ⭐️ What you need - 5+ years of hands-on experience in software quality assurance or engineering, with a strong focus on testing complex distributed systems or AI/ML applications. - 5+ years of experience working with GitHub actions - Proficiency in programming languages like Python or Typescript for test automation, and experience with modern testing frameworks such as Playwright. - Solid understanding of AI/ML concepts, including model evaluation metrics, data pipelines, and the unique challenges of testing generative AI outputs. - Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) in a CI/CD environment is a big plus. - Exceptional analytical skills to dissect complex problems and a keen eye for detail, ensuring no bug goes unnoticed. - A collaborative spirit that helps you Connect cross-functional teams to common quality goals, Challenge existing assumptions to build better systems, and Own the end-to-end quality of our products. - Demonstrated ability to drive initiatives independently and thrive in a fast-paced, evolving startup environment. 🍩 Benefits & perks (UK full-time employees): - Generous PTO, plus company holidays - Comprehensive medical and dental insurance - Paid parental leave for all parents (16 weeks) - Fertility and family planning support - Early-detection cancer testing through Galleri https://www.galleri.com/partner/writer - Competitive pension scheme and company contribution - Annual work-life stipends for: - Wellness stipend for gym, massage/chiropractor, personal training, etc. - Learning and development stipend - Company-wide off-sites and team off-sites - Competitive compensation and company stock options
Software engineer, generative AI (UK)
🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role Imagine stepping into a role where your code directly empowers the world's largest enterprises to safely adopt superintelligence. As a software engineer, generative ai at WRITER, you'll be at the forefront of expanding human capacity by building the secure, scalable foundation that allows our generative AI solutions to thrive in complex corporate environments. The impact of this work is massive – for example, in the consumer packaged goods industry alone, our AI adoption is driving 69% revenue increases and 72% cost reductions. This role is designed for a well-rounded engineering generalist who leans heavily into generative AI while bringing a whole-systems mindset to architectural design. If you thrive on proactivity without red tape and love owning projects from proposal to deployment, you'll shape the future of AI and contribute to a product that’s changing how the world works. This is a hybrid role based out of our San Francisco, New York City, or London hubs. You'll report to an engineering director or a senior engineering manager. * We are open to hiring for this role at multiple levels, from senior to staff software engineer, with compensation ranges scaled to match your experience and expertise. 🦸🏻♀️ What you'll do - Design and develop robust, secure, and scalable generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation - Build and optimize high-performance, low-latency APIs and microservices to integrate advanced AI models and sophisticated agentic workflows into our core platform - Act as a whole-systems thinker by making meaningful system design decisions and owning the architecture of core platform components from initial proposal through production deployment - Implement and maintain responsive user interfaces using technologies like React and TypeScript to deliver intuitive user experiences and bridge the gap between backend services and frontend enablement - Drive proactivity without red tape by clearly communicating changes, plans, and proposals to cross-functional teams and collaborating closely with product managers, data scientists, and DevOps engineers - Partner with DevOps teams to build continuous deployment, logging, and monitoring systems that ensure top-tier performance, security, and reliability across distributed workloads ⭐️ What you need - 3-5+ years of hands-on experience as a software engineer with a strong emphasis on Python development in production environments - Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open-source agentic frameworks - Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure, and containerization with Docker and Kubernetes - Solid grasp of modern web technologies including FastAPI, Asyncio, database systems like PostgreSQL, and hands-on experience leveraging AI developer tooling like Claude, Cursor, or GitHub Copilot to accelerate your engineering workflows - Exposure to enterprise architecture including practical experience implementing IAM, SSO, SAML, OAuth, OIDC, RBAC, robust security best practices, or building services for enterprise administration and billing systems - A Connect mindset that thrives in collaborative settings where you actively engage with cross-functional teams and mentor other engineers, a Challenge spirit that drives you to tackle complex technical hurdles and proactively suggest innovative improvements, and an Own attitude where you take full accountability for delivering high-quality, resilient, and scalable code from conception to production 🍩 Benefits & perks (UK full-time employees): - Generous PTO, plus company holidays - Comprehensive medical and dental insurance - Paid parental leave for all parents (16 weeks) - Fertility and family planning support - Early-detection cancer testing through Galleri https://www.galleri.com/partner/writer - Competitive pension scheme and company contribution - Annual work-life stipends for: - Wellness stipend for gym, massage/chiropractor, personal training, etc. - Learning and development stipend - Company-wide off-sites and team off-sites - Competitive compensation and company stock options
Software engineer, generative AI
🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role Imagine stepping into a role where your code directly empowers the world's largest enterprises to safely adopt superintelligence. As a software engineer, generative ai at WRITER, you'll be at the forefront of expanding human capacity by building the secure, scalable foundation that allows our generative AI solutions to thrive in complex corporate environments. The impact of this work is massive – for example, in the consumer packaged goods industry alone, our AI adoption is driving 69% revenue increases and 72% cost reductions. This role is designed for a well-rounded engineering generalist who leans heavily into generative AI while bringing a whole-systems mindset to architectural design. If you thrive on proactivity without red tape and love owning projects from proposal to deployment, you'll shape the future of AI and contribute to a product that’s changing how the world works. This is a hybrid role based out of our San Francisco, New York City, or London hubs. You'll report to an engineering director or a senior engineering manager. We are open to hiring for this role at multiple levels, with compensation ranges scaled to match your experience, expertise, and the scope of the role. 🦸🏻♀️ What you'll do - Design and develop robust, secure, and scalable generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation - Build and optimize high-performance, low-latency APIs and microservices to integrate advanced AI models and sophisticated agentic workflows into our core platform - Act as a whole-systems thinker by making meaningful system design decisions and owning the architecture of core platform components from initial proposal through production deployment - Implement and maintain responsive user interfaces using technologies like React and TypeScript to deliver intuitive user experiences and bridge the gap between backend services and frontend enablement - Drive proactivity without red tape by clearly communicating changes, plans, and proposals to cross-functional teams and collaborating closely with product managers, data scientists, and DevOps engineers - Partner with DevOps teams to build continuous deployment, logging, and monitoring systems that ensure top-tier performance, security, and reliability across distributed workloads ⭐️ What you need - 3-5+ years of hands-on experience as a software engineer with a strong emphasis on Python development in production environments - Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open-source agentic frameworks - Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure, and containerization with Docker and Kubernetes - Solid grasp of modern web technologies including FastAPI, Asyncio, database systems like PostgreSQL, and hands-on experience leveraging AI developer tooling like Claude, Cursor, or GitHub Copilot to accelerate your engineering workflows - Exposure to enterprise architecture including practical experience implementing IAM, SSO, SAML, OAuth, OIDC, RBAC, robust security best practices, or building services for enterprise administration and billing systems - A Connect mindset that thrives in collaborative settings where you actively engage with cross-functional teams and mentor other engineers, a Challenge spirit that drives you to tackle complex technical hurdles and proactively suggest innovative improvements, and an Own attitude where you take full accountability for delivering high-quality, resilient, and scalable code from conception to production 🍩 Benefits & perks (US Full-time employees) - Generous PTO, plus company holidays - Medical, dental, and vision coverage for you and your family - Paid parental leave for all parents (16 weeks) - Fertility and family planning support - Early-detection cancer testing through Galleri https://www.galleri.com/partner/writer - Flexible spending account and dependent FSA options - Health savings account for eligible plans with company contribution - Annual work-life stipends for: - Wellness stipend for gym, massage/chiropractor, personal training, etc. - Learning and development stipend - Company-wide off-sites and team off-sites - Competitive compensation, company stock options and 401k WRITER is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. By submitting your application on the application page, you acknowledge and agree to WRITER's Global Candidate Privacy Notice https://writer.com/legal/candidate-privacy-notice/.
Vice President, AI Data
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. ABOUT US Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. The role At Wayve, we are building AI that learns to drive from experience. We do not hand-code cars to drive. We train our models from data gathered across the real world, making our ability to identify, understand and learn from the right data fundamental to everything we build. We are looking for a VP of Data to lead the data strategy behind our autonomous driving technology. This is a senior engineering leadership role with end-to-end ownership of how Wayve uses data to improve our AI. You will determine what data we need, how we acquire it, how we understand and enrich it, and ultimately how we turn it into measurable improvements in model performance. The scale and shape of the problem is unique. Our data comes from our own vehicles, OEM programmes, partners and external sources, spanning different vehicles, sensors, markets and driving environments. Within that corpus, the most valuable examples are often the hardest to find: rare behaviours, unusual interactions, safety-critical events and the long tail of real-world driving. Your job is not simply to build the systems that process this data. It is to decide what data matters and why, and build the strategy, organisation and learning loop that allows Wayve to learn from it faster. You will lead Wayve’s Data organisation and provide senior ownership for data within Engineering, partnering closely across AI, Science, Validation, Product, Compute and our commercial teams. Key Responsibilities - Own Wayve’s data strategy: Set the strategy across the complete AI learning cycle, determining what data we need and how it should drive model performance, from foundation model training through specialised driving capabilities and production programmes. - Build the data flywheel: Own the learning loop from real-world signals and model behaviour through data discovery, curation and enrichment into training, evaluation, deployment and measurement. - Find the data that matters: Develop intelligent approaches to discovering rare, surprising and safety-critical scenarios within extremely large datasets, using techniques such as embeddings, semantic search, learned representations and model-driven data selection. - Lead data acquisition and enrichment: Define how Wayve collects, buys, generates and enriches data across our own fleet, OEM programmes, partners and external sources, balancing coverage, quality, speed and economics. - Connect data investment to model performance: Establish how we measure the value of data and make rigorous trade-offs across quality, accuracy, speed, cost and scale, ensuring investment is focused where it creates the greatest impact. - Scale our data strategy globally: Build an approach that supports multiple OEMs, vehicle platforms, sensor configurations, geographies and regulatory environments while maintaining a scalable global architecture. - Build and lead the organisation: Lead and develop a high-performing, multidisciplinary Data organisation, partnering closely with AI, Science, Validation, Product, Compute, Finance and Commercial teams. About You You are a senior technical leader who has operated at the intersection of AI, data and large-scale model development. You can set direction in ambiguity and make high-quality decisions without perfect information. You are equally comfortable going deep into the characteristics and value of a dataset, challenging how a team measures model improvement, making significant investment decisions, or defining how an organisation should operate. You have strong technical judgement, but think about data through the impact it has on the intelligence and performance of the system, rather than simply the infrastructure required to store and process it. You can hold the full system in your head while still going deep on the details that matter. Essential - Significant engineering leadership experience, with a track record of building and leading high-performing technical organisations. - Deep technical expertise in computer vision, video, multimodal AI or related perception problems. - Experience leading large-scale data capabilities that directly influence model training, evaluation and performance. - Strong intuition for what makes data valuable, with experience in data discovery, selection, curation and enrichment at scale. - Strong technical and commercial judgement, including making trade-offs across quality, speed, cost, scale and build-versus-partner decisions. - Ability to move between strategy and technical detail, set direction in ambiguity, and influence effectively across senior technical and business stakeholders. Desirable Experience in one or more of the following areas would be a strong advantage: - Autonomous driving, robotics or embodied AI. - Large-scale video, multimodal or foundation model training. - Semantic search, embeddings, active learning, auto-labelling or other approaches to intelligent data selection and enrichment. - Large-scale real-world data acquisition across fleets, customers, partners or multiple geographies. This is a full-time role based in either our in Sunnyvale or London office. At Wayve we want the best of all worlds, so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. A quick, honest note before you apply. Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/ DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
Technical Lead Manager, Synthetic Data
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Simulation Teams Simulation is advancing our end-to-end autonomous driving research. The team’s mission is to accelerate our journey to AV2.0 by incubating capabilities that become company-level advantages. GAIA, our generative world models, and the synthetic data they produce, are one of those. This role leads Synthetic Data within Simulation. The team exists to dramatically reduce our dependency on expensive and time-consuming on-road data collection by turning generative world models (models like GAIA-3) into a production engine for training-grade experience. When we can restage real driving onto a camera rig that does not exist yet, rewrite ego motion to create scenarios we have never encountered, and land that data in the same training stack we use for real driving, we can train, evaluate and deploy on vehicles and in geographies we have barely collected from. As Tech Lead Manager, you’ll lead a high-performing team of machine learning engineers and help us answer questions like: can we train and validate a driving model for a vehicle platform before the fleet exists, can synthetically generated data replace scarce real-world data for training and evaluation, and how quickly can we deploy autonomous driving in a geography where we’ve never collected AV data? 🧠 Your day-to-day - Algorithmic and system design: define approach to GAIA generation, system design of the synthetic data pipeline and controllability engine, focus on efficiency and quality. - Cross-team collaboration: aligning with driving-model owners and with evaluation and safety team on utility and scalability of generated data. - Mentorship / async review: reviewing a teammate’s experimental design, PR, or ablation write-up and giving direct feedback. - 1:1s and feedback: building rapport and managing your direct reports. - Up to date with state of the art: keeping current on video generation, camera transfer, distillation — insofar as it changes a checkpoint or a mix we ship. - Strategy: leading or joining strategic discussions on the synthetic data roadmap, safety case and platform bring-up sequencing. 🧩 What you’ll be working on - Architect the future — set the technical direction for how we post-train and condition world models for synthetic-data capabilities (rig transfer, pose transfer, controllability), holding a high bar for what counts as training-grade generation. - Own the loop end to end — make sure generation, evaluation and training stay one system: from checkpoint and config, through large-scale GPU inference, to artefacts that land in driving-model training with reproducible lineage. - Get hands-on when it matters — lead from the front on key components, codebases and experiments. - Push throughput and yield — drive inference optimisation (distillation, few-step sampling, KV caching, step count), valid-generation rate, and self-serve workflows so model developers can request synthetic sets without a specialist in the loop. - Disrupt thoughtfully — challenge assumptions about where synthetic data pays off, ask sharp questions, and champion bold ideas that move us beyond incremental gains. - Make things happen — lead a high-performing, cross-functional team of ML engineers and applied scientists working across generative modelling, generation infrastructure and training. Drive quarterly planning and execution in a high-ambiguity environment where the target moves. - Align and connect — collaborate with world-model researchers, platform and infra engineers, driving-model owners and evaluation so synthetic data is integrated into the broader stack, not delivered over a wall. Manage upwards and laterally to align your team’s goals with company priorities and OEM programme timelines. - Architect teams — grow and structure a resilient team by hiring top talent, designing effective operating models, and fostering a sense of belonging regardless of location. Cultivate a strong, inclusive culture rooted in scientific rigour, collaboration and curiosity. - Level up — coach and mentor team members, tailoring growth plans to individual strengths and aspirations. Lead by example through technical engagement and clear feedback. - Champion change — navigate your team through evolving research priorities and fast-moving execution, maintaining stability and trust through uncertainty. 🙌 You should apply if - 5+ years of experience in ML engineering or applied research roles, with a track record of training and shipping neural networks — not only operating data platforms. - 4+ years of people management experience, including direct reports and cross-functional project ownership. - Deep knowledge of generative modelling (diffusion, flow matching, autoregressive, or VAEs) applied to video or other high-dimensional temporal data. - Hands-on experience with video, generative or world models — for example video generation, novel-view synthesis, neural rendering, or controllable generation. - Working knowledge of cameras and 3D geometry (multi-camera rigs, intrinsics/extrinsics, warps and reprojection) and why they break generation or downstream training. - Evidence of closing the loop: taking generated or simulated data into a trained downstream model and measuring impact through mix ratios, ablations and failure analysis. - Experience operating generation or training at real scale — multi-GPU jobs, workflow orchestration, large video artefacts — and making that path reliable. - Strong Python and PyTorch engineering fundamentals, and experience building research-grade production tools. - Excellent communication skills and a passion for coaching and mentoring others. - You balance technical depth with people leadership. You know when to lead from the front and when to empower your team. - You embrace ambiguity and help your team make sense of it, keeping clarity and momentum through uncertainty. 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement. More about Wayve: 🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility. How we work 💻- Locations & Flexible Working: Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives. 🔍 The Interview Process: Our process is clear and respectful of your time: - Initial call / recruiter screen (30 mins) - Competency Interviews (Programming/Pytorch Debugging and hiring manager interview; 2 hours total) - Deep-dive technical interviews (Systems & domain-specific interviews; 3 hours total) - Final interview: Mission & values alignment (45 mins).. We’ll always explain the format and work around your availability. What’s in it for you (Location dependant): 💰 Salaries benchmarked against the market annually 📈 Meaningful equity, sharing in the ownership and long term success of Wayve ✈️ Relocation support and visa sponsorship where applicable ✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs 📚 Learning and development budgets with support for training, conferences and growth 🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more A quick, honest note before you apply. Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/ DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
Senior ML Performance Engineer, Inference Optimisa...
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams Our ML performance team optimises inference for edge accelerators and GPUs, so large transformer-based models run efficiently on low-cost, low-power in-vehicle compute. We work closely with model, platform and deployment teams to turn research models into reliable production systems for Wayve's driving product. 🧠 Your day-to-day This is a hands-on role across ML systems, compilers, runtimes, kernels and embedded deployment. You'll find bottlenecks, implement performance improvements, and work with model developers on performance trade-offs so deployment-aware decisions are made early. 🧩 What you'll be working on - Profiling inference performance across model graphs, compiler/runtime behaviour, kernel execution and memory movement - Implementing and validating optimisations in compilers, runtimes and/or kernels, including fusion, scheduling, quantisation-aware performance and custom kernels - Building benchmarking and regression tests to track performance across models, devices and software releases - Optimising for edge targets such as NVIDIA Orin/Thor and Qualcomm platforms - Contributing to team tooling, documentation and technical discussions around ML performance 🙌 You should apply if - You have experience improving performance in production or production-adjacent systems with latency, memory, bandwidth, power, thermal or cost constraints - You have strong hands-on experience with at least one relevant stack, such as TensorRT, CUDA, Qualcomm QNN, Triton or OpenCL - You are comfortable working from high-level model behaviour down to kernel/runtime-level execution - You have strong software engineering fundamentals, including debugging, profiling, testing and maintainable code - You communicate clearly and work well across ML, systems and deployment teams Nice to have: - Experience deploying or benchmarking ML models on embedded or edge devices - Familiarity with NVIDIA and/or Qualcomm SoCs and performance tooling - Python and C++ proficiency - Experience supporting other engineers or contributing to technical direction within a small team 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement. More about Wayve: 🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility. How we work 💻- Locations & Flexible Working: Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives. 🔍 The Interview Process: Our process is clear and respectful of your time: - Initial call / recruiter screen - Deep-dive technical interviews [programming, system design & domain-specific interviews; 3 hours total] - Final interview: mission & values alignment We’ll always explain the format and work around your availability. What’s in it for you (Location dependant): 💰 Salaries benchmarked against the market annually 📈 Meaningful equity, sharing in the ownership and long term success of Wayve ✈️ Relocation support and visa sponsorship where applicable ✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs 📚 Learning and development budgets with support for training, conferences and growth 🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more A quick, honest note before you apply. Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/ DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
Machine Learning Software Engineer
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Science Teams We are looking for an ML Software Engineer to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Science as a founding member. MEGA is building foundation models for general-purpose robots: models that learn from large-scale video, language, and robot-interaction data, then generalize across tasks and embodiments, including mobile manipulators, dual-arm platforms, and humanoids. Our aim is to build agents that can perceive, reason about, and act reliably in the physical world. You will design and build the software systems that enable MEGA’s machine learning research. This includes scalable ML pipelines, data and training infrastructure, and the shared tools and abstractions that allow researchers to move quickly from an idea to a reliable experiment. The role sits close to the models and data. You will work with large-scale video and robotics datasets, modern ML frameworks, and increasingly large models, building systems that remain reliable and maintainable as the research program grows. You will be a core member of the MEGA team, owning key parts of the software and ML infrastructure that underpin the research program, and will help shape how the team develops and operates its ML stack as the program grows. 🧠 Your day-to-day - Design and maintain scalable pipelines for data ingestion, model training, evaluation, and experimentation. - Build reusable interfaces and shared tooling across data, models, training, evaluation, and downstream robotics workflows. - Partner with researchers to translate evolving model and experiment needs into practical software systems. - Diagnose and resolve performance, reliability, and usability bottlenecks across large-scale ML workloads. - Raise the quality of the shared codebase through strong architecture, testing, documentation, and engineering standards. - Support distributed training and data processing across large video, language, and robot-interaction datasets. 🧩 What you’ll be working on - Design, build, and maintain scalable ML pipelines for data ingestion, model training, evaluation, and related research workflows. - Build software systems that allow ML workloads to scale to larger datasets, larger models, and more experiments. - Develop clean and reusable interfaces between data, models, training, evaluation, and downstream robotics workflows. - Own and improve the health of the MEGA codebase, including software architecture, testing, reliability, maintainability, and engineering standards. - Identify and resolve performance, reliability, and usability bottlenecks across ML workflows. - Build and maintain infrastructure that supports multiple researchers and ML projects without unnecessarily slowing down iteration. - Work closely with researchers to understand the requirements of new models and experiments, and translate those requirements into practical software solutions. - Build and use distributed training and data-processing pipelines for large models and large multimodal datasets. 🙌 You should apply if - Strong software engineering skills and experience building high-quality, maintainable software. - Experience building and maintaining machine learning pipelines or infrastructure, such as data ingestion, training, evaluation, or experiment workflows. - Experience designing software systems and abstractions that are reliable, reusable, and able to evolve as requirements change. - Hands-on experience with modern machine learning frameworks and a good understanding of how ML training and experimentation workflows operate. - Strong debugging skills and the ability to investigate problems across complex ML systems. - Experience with software testing, code quality, and engineering practices for maintaining a healthy shared codebase. - Experience working with large datasets, large models, or other computationally demanding ML workloads. - Ability to collaborate closely with researchers and engineers and translate research requirements into practical software systems. 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement. More about Wayve: 🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility. How we work 💻- Locations & Flexible Working: Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives. 🔍 The Interview Process: Our process is clear and respectful of your time: - Initial call / recruiter screen (30 mins) - Competency Interviews (Programming and hiring manager interview; 1.5 hours total) - Deep-dive technical interviews (Systems & domain-specific interviews; 3 hours total) - Final interview: Mission & values alignment (45 mins). We’ll always explain the format and work around your availability. What’s in it for you (Location dependant): 💰 Salaries benchmarked against the market annually 📈 Meaningful equity, sharing in the ownership and long term success of Wayve ✈️ Relocation support and visa sponsorship where applicable ✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs 📚 Learning and development budgets with support for training, conferences and growth 🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more A quick, honest note before you apply. Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/ DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
Full Stack Software Engineer, Evaluation Tools
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams The Evaluation Tools group builds the internal products that accelerate the full AI Driver development loop, from defining a test to debugging model behaviour. Model developers, researchers and QA engineers across Wayve depend on our tools to understand driving performance and scale evaluation to millions of scenarios, and every major model release runs through them. You’ll join the Search & Agents squad in Sunnyvale. We build the search, scenario mining and agentic tooling that lets anyone find the right driving scenarios and turn them into tests without writing SQL. Our work is the entry point to a fully agentic development loop: identify an issue → mine for scenarios → build and run a test suite → root-cause the failure → retrain → repeat. You’ll work across the stack and own features end-to-end: talking to users, shaping ideas, building robust software, and validating impact. Evaluation is an evolving challenge, so you’ll also have plenty of opportunity to define new projects as user needs emerge. 🧠 Your day-to-day - Build fullstack features across search, scenario mining and agentic tooling. - Talk to model developers and researchers, and define how you will measure success before building. - Take the scenario mining framework from prototype to production scale. - Extend our agent tooling so agents can run evaluation workflows end to end. - Work with large-scale data systems (Databricks, Spark) in an established codebase. - Own the reliability and maintainability of what you ship. 🧩 What you’ll be working on - Build fullstack features across search, scenario mining, agentic tooling, and the web applications our users work in to curate scenarios and build test suites. - Work directly with users to understand pain points, then define and measure what success looks like (adoption, time saved, reliability) before you build. - Ship high-quality software with strong attention to reliability, performance and maintainability. - Contribute to architectural decisions that scale across the team’s products. - Use AI tools to improve how we build, from speeding up development to refining team workflows and product quality. 🙌 You should apply if Essential - Strong development skills in Python, TypeScript, and JavaScript, with experience using React or similar front-end frameworks - Strong SQL skills with a solid understanding of database design and optimisation - Experience designing and building production-level fullstack systems and reliable, high-performance APIs - Track record of building robust, maintainable systems and applying engineering best practices - Excellent communication and collaboration skills, including working effectively across time zones - Comfortable working independently in a fast-paced, high-context, ambiguous environment - You are a power user of AI development tools and have a mindset for building AI-augmented workflows Desirable - Experience with search, embeddings or retrieval systems - Experience with the Databricks platform, and large-scale data processing with Spark or similar - Experience with job orchestration frameworks such as Flyte - Experience building agentic or LLM-powered developer tools (e.g. MCP servers) - Experience building tools for technical users (ML, robotics, infrastructure) - Experience with scientific data visualisation or complex data interfaces 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement. More about Wayve: 🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility. How we work 💻- Locations & Flexible Working: Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives. 🔍 The Interview Process: Our process is clear and respectful of your time: - Initial call / recruiter screen (30 mins) - Competency Interviews (Programming and hiring manager interview; 2 hours total) - Deep-dive technical interviews (Systems & domain-specific interviews; 2 hours total) - Final interview: Mission & values alignment (45 mins). We’ll always explain the format and work around your availability. What’s in it for you (Location dependant): 💰 Salaries benchmarked against the market annually 📈 Meaningful equity, sharing in the ownership and long term success of Wayve ✈️ Relocation support and visa sponsorship where applicable ✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs 📚 Learning and development budgets with support for training, conferences and growth 🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more A quick, honest note before you apply. Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/ DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
Staff Software Engineer, DUE Experience
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. You will: - Lead the architectural design and hands-on development of advanced Agentic AI systems, focusing on multi-agent orchestration, tool execution, and complex reasoning loops for event triage. - Engineer scalable agentic workflows using modern LLM orchestration frameworks to fully automate and augment triage capabilities for Engineering and SWQOps. - Design and deploy stateful agentic infrastructure, including long-term memory management (RAG, vector databases), semantic routing, and custom internal tool integrations. - Collaborate with cross-functional partner teams to embed autonomous agents directly into the Waymo Driver evaluation lifecycle. - Mentor engineers within DUE Experience on agentic development patterns, and prompt engineering - Tackle broad, ambiguous automation problems by breaking them down into actionable multi-agent projects and leading the technical execution of the roadmap. You have: - Significant experience (typically 8+ years) in software engineering, with a focus on designing and building large-scale, complex distributed systems. - Deep expertise in applied LLMs and Agentic AI development, with a proven track record of building multi-agent systems, reasoning engines, and autonomous workflows. - Strong proficiency with agent orchestration frameworks and advanced prompt engineering. - Proven ability to execute technical strategy, influence partner teams, and drive end-to-end development of AI-native applications in ambiguous domains. - Excellent communication and collaboration skills, with the ability to align cross-functional stakeholders on agentic concepts and system limitations. - Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience. We prefer: - Master's or PhD in Computer Science or a related field, with a specialization in AI/ML or a related area. - Experience developing custom tools/plugins for agents, semantic routers, and implementing complex multi-agent collaborative patterns. - Familiarity with autonomous vehicle simulation, testing, or evaluation domains. - Proficiency in C++ and Python, with experience building production-grade microservices and pipelines. - Experience working with large-scale data processing, knowledge graphs, and distributed systems. - Familiarity with Google's or Waymo's internal AI/ML platforms and infrastructure. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $251,000 - $310,000 USD
Staff Machine Learning Infrastructure Engineer, Si...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulation ML Infrastructure team builds scalable AI/ML infrastructure to accelerate the Simulator team in sustainably innovating and building state of the art simulations of realistic environments for the testing and training of the Waymo Driver. To increase the fidelity and steerability of the simulations, we employ large foundation models trained on massive datasets to model the real world, including but not limited to, realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.), roads, traffic control systems, and weather etc. We seek an experienced Senior Machine Learning Infrastructure Engineer to lead the development of advanced AI/ML infrastructure for multi-billion parameter foundation models in ML accelerator-friendly simulations. Your expertise in massive model scaling, ML accelerators, and distributed training will be required for designing and scaling our systems. This role reports to an Engineering Manager. You will: - Be part of a world-class, high-performing research engineering team to advance the state of the art of ultra realistic multi-agent simulations using foundation models. - Collaborate closely with the core Google DeepMind and Waymo Realism Modeling teams in London, and Waymo Oxford to use the large models to improve sim realism. - Provide deep technical leadership on large-scale ML model architectures, especially for autonomous vehicle models. Work at the intersection of data engineering, model development, and deployment, and provide guidance on architectural decisions and technical directions. Own large, complex systems, driving architectures that meet technical and business objectives. - Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation and model training. - Collaborate cross-functionally to derive performance and system-level requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component alignment. - Mentor junior engineers, growing their expertise and fostering a collaborative culture. You have: - BS in Computer Science, Robotics, similar technical field of study, or equivalent practical experience - 5+ years of professional software engineering experience, with at least 3 years in machine learning infrastructure such as developing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model. We prefer: - MS in Computer Science, Robotics, similar technical field of study, or equivalent practical experience - 10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model. - Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, or similar frameworks. - Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks. - Deep understanding of state-of-the-art machine learning models such as auto-regressive transformers and familiarity with custom-kernels for diverse h/w compute based efficiency. - Practical familiarity in Autonomous Driving, Simulations, and ML accelerators is a huge plus. The expected base salary range for this full-time position is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range £155,000 - £163,000 GBP
Staff Machine Learning Engineer, Maneuvering Tech
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Driver Refinement and Validation’s (DRV) mission is to build upon the high-quality ML Driver developed by Driver Intelligence, refining its performance to improve autonomous driving in specific, complex real-world contexts and problem areas (e.g., Ride-Hailing contexts). It aims to ensure that the Waymo Driver always computes safe, compliant, comfortable, and useful plans. As an Engineer in DRV, you will bridge the gap between cutting-edge machine learning and real-world vehicle performance, engineering the validation and onboard systems that ensure the autonomous vehicle reliably executes intelligent and predictable maneuvers. You will: - Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo’s business - Fine-tune, adapt, and benchmark state-of-the-art generative models to improve autonomous vehicle perception, motion prediction, and trajectory planning - Write high-quality, scalable, and thoroughly tested code to bring cutting-edge ML into production - Partner with world-class engineers and product managers to deliver safe and smooth autonomous vehicle behaviors You have: - MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience - 8+ years of industry experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments - Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities - Expertise with modern deep learning frameworks, such as JAX or PyTorch We prefer: - Experience in deep learning, reinforcement learning, and ML systems - Domain expertise in solving prediction, behaviors, motion planning, or related robotics problems - ML post-training experience - Prior industry experience (e.g. internships) in applied ML or software development - Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP) The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $251,000 - $310,000 USD
Sr. Staff Software Engineer, DUE Experience
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. In this hybrid role, you will report to the Engineering Manager. You will: - Define and drive the technical vision and architectural strategy for autonomous, multi-agent systems within the DUE Experience team, focusing on transformative improvements in event triage. - Lead the exploration and application of state-of-the-art agentic technologies to automate complex triage workflows, shifting paradigms from static LLM generation to dynamic reasoning, planning, and execution. - Architect, design, and guide the implementation of scalable, robust agentic frameworks capable of dynamic tool use, self-reflection, and multi-step orchestration. - Collaborate across teams to identify opportunities where agentic workflows and specialized AI agents can autonomously navigate and impact the broader Waymo Driver evaluation lifecycle. - Mentor and provide technical guidance to engineers within DUE Experience and partner teams, fostering innovation and engineering excellence in agentic design patterns. - Identify and advocate for the broad problem(s) worth solving, turning big-picture concepts into actionable projects and roadmaps for human-on-the-loop autonomous systems. You have: - Extensive experience (typically 10+ years) in software engineering, with a significant focus on architecting and building large-scale, complex systems. - Deep expertise in Artificial Intelligence and Machine Learning, with heavy, hands-on experience building autonomous agents, multi-agent orchestration systems, and integrating LLMs with external tools/APIs. - Proven ability to define technical strategy, influence senior leadership, and drive execution across multiple teams in ambiguous and rapidly evolving domains. - A strong track record of technical leadership, including designing and implementing novel agent-based solutions. - Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences. - Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience. We prefer: - PhD in Computer Science or a related field, with a specialization in AI/ML or a related area. - Experience with agentic frameworks, knowledge graphs, and reasoning engines. - Familiarity with autonomous vehicle simulation, testing, or evaluation domains. - Proficiency in C++ and experience with building production-grade services. - Experience working with large-scale data processing and distributed systems. - Familiarity with Google's or Waymo's internal AI/ML platforms and infrastructure. Disclosure for WA Based & Remote Roles: In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year US Remote Only: Please note that Waymo may not be able to employ remotely in all US locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $298,000 - $368,000 USD
Software Quality Operations Specialist, Domain Exp...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Software Quality Operations (SWQOps) team is at the heart of ensuring the safety, reliability, and quality of the Waymo Driver. Our mission is to build an adaptable and scalable operation, increasingly powered by AI, to deliver the crucial insights necessary to confidently deploy and grow Waymo's autonomous vehicle service. Why This Team is Essential to Waymo's Success: Waymo is undergoing unprecedented growth, rapidly expanding into new cities (targeting ~20 new cities by EOY 2026) and launching new vehicle platforms. SWQOps, especially our Technical Specialists, plays a critical role in this expansion, making it possible to scale safely and efficiently. We are on the front lines of: - Supporting the development of a single, automated, end-to-end machine learning flywheel for the entire Waymo Driver. A successful flywheel will be the core engine for scaling our technology, enabling faster ODD expansion, quicker remediation of driving issues, and a significant reduction in the engineering effort required to maintain and improve the driver - De-risking New Deployments: Through meticulous triage of driving events, issue discovery, and continuous field monitoring, SWQOps provides early warnings and critical insights. This "early intervention in RO issue detection" ensures operational resilience and safety, particularly in new and complex environments, which is critical as Waymo enters multiple new cities and ramps up platforms like W12 - Enabling Market Expansion: Our team is deeply integrated into every stage of Waymo's market entry framework, from initial city evaluation (OK2Plan) to scaling operations (OK2Scale). We provide the necessary data analysis, policy development, and quality assurance to unblock critical milestones, preventing slowdowns in market expansion velocity - Driving Engineering Velocity: By handling the vital work of performance evaluation, issue deep-dives, and data set curation, SWQOps collaborates heavily and allows Waymo's Engineering, SysEng, Simulation, and Data Science teams to focus on their core tasks of developing and improving the Waymo Driver You will: - Partner with Engineering to design, test, and deploy cutting-edge Machine Learning (ML) and Generative AI (Gen-AI) models and tools to drive improvements in issue discovery & detection, triage efficiency, and quality assurance - Leverage AI-powered insights and traditional triage signals to proactively identify emerging on-road issue trends, new risk scenarios, and edge cases. Develop and refine data-driven strategies for issue discovery and monitoring, enhanced by ML model outputs - Serve as the key link between AI/ML development and operational execution. Define and document new policies, guidelines, and Standard Operating Procedures (SOPs) that integrate AI tools and insights into daily vendor workflows. - Design and implement robust quality control processes for both human and AI-generated outputs. Perform meta-quality checks, validate the integrity of vendor work, and provide feedback to improve both human and model performance - Act as the subject matter expert for our Software Quality Operations, working closely with stakeholders, program leads, and vendor teams to ensure seamless adoption and maximum impact of AI/ML advancements in our quality processes. Be the trusted source for creating and updating technical policies, guidelines, and standard operating procedures for new scopes, platforms, and driving signals - Provide technical leadership and consultation to stakeholders to enhance our workflows and quality. You'll be at the forefront of identifying and escalating issues with our tools, providing technical requirements to engineering, and driving user testing to support the development and deployment of new tooling features - Scale workflow from 16/5 to 24/7 coordinating with external stakeholders, vendor team, and FTE team You have: - BS/BA degree and 4 years of relevant work experience in QC or AV Software Quality Operations - Increased competency in supporting all phases of the machine learning development life-cycle: data preparation, training, validation, deployment, and continuous monitoring - Experience with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics - Ability to quickly learn and implement new concepts and utilize proprietary tools. Strong understanding of driving rules and regulations - A proven ability to work in a fast-paced, high-stress environment while maintaining good judgment - Excellent communication and interpersonal skills to effectively collaborate with a wide range of individuals in a diverse and dynamic work environment - Demonstrated strong execution with ability to drive outcomes - Ability to effectively and efficiently communicate with cross-functional stakeholders We prefer: - Experience working with offshore teams / multiple local operations hubs - Competency in LLM / transformer models, and / or ML for robotics domain experience - Basic SQL querying and PLX coding experience - Using subject matter expertise for results analysis and direct customer consultation in the development of new and improved solutions - Self-motivated with basic skills in task planning and time management - Experience with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics - Experience assessing AV safety performance In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: - Health, dental, vision, life, disability insurance - Retirement Benefits: 401(k) with company match - Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment - Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) - Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks - Baby Bonding Leave: 18 weeks - Holidays: 13 paid days per year ((Remote jobs only - Please note that Waymo may not be able to employ remotely in all locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.)) The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $120,000 - $151,000 USD
Software Quality Operations Specialist
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Software Quality Operations (SWQOPS) team is at the heart of ensuring the safety, reliability, and quality of the Waymo Driver. Our mission is to build an adaptable and scalable operation, increasingly powered by AI, to deliver the crucial insights necessary to confidently deploy and grow Waymo's autonomous vehicle service. Waymo is experiencing unprecedented growth, rapidly expanding into new cities and launching new vehicle platforms. SWQOps, particularly our Technical Specialists, are critical to this expansion, enabling us to scale safely and efficiently. Why this team is Essential to Waymo's Success: In this role you will: - Partner with Engineering to design, test, and deploy cutting-edge Machine Learning (ML) and Generative AI (Gen-AI) models and tools to drive step-change improvements in issue discovery & detection, triage efficiency, and quality assurance. - Leverage AI-powered insights and traditional triage signals to proactively identify emerging on-road issue trends, new risk scenarios, and edge cases. Develop and refine data-driven strategies for issue discovery and monitoring, enhanced by ML model outputs - Serve as the key link between AI/ML development and operational execution. Define and document new policies, guidelines, and Standard Operating Procedures (SOPs) that integrate AI tools and insights into daily vendor workflows. - Design and implement robust quality control processes for both human and AI-generated outputs. Perform meta-quality checks, validate the integrity of vendor work, and provide feedback to improve both human and model performance. - Act as the subject matter expert for our Software Quality Operations, working closely with stakeholders, program leads, and vendor teams to ensure seamless adoption and maximum impact of AI/ML advancements in our quality processes. Be the trusted source for creating and updating technical policies, guidelines, and standard operating procedures for new scopes, platforms, and driving signals - Provide technical leadership and consultation to stakeholders to enhance our workflows and quality. You'll be at the forefront of identifying and escalating issues with our tools, providing technical requirements to engineering, and driving user testing to support the development and deployment of new tooling features. - A proven ability to work in a fast-paced, high-stress environment while maintaining good judgment. - Excellent communication and interpersonal skills to effectively collaborate with a wide range of individuals in a diverse and dynamic work environment. You have: - BS/BA degree or 4 years of relevant work experience in AV Software Quality Operations - Increased competency in supporting all phases of the machine learning development lifecycle, from data preparation and training to validation, deployment, and continuous monitoring. - Experience with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics. - Ability to quickly learn and implement new concepts and utilize proprietary tools. Strong understanding of driving rules and regulations. - Must have the ability to provide occasional on-call availability for evenings, weekends, and holidays, as well as the flexibility to attend meetings outside of standard hours to collaborate with our global team. We prefer: - Demonstrated strong execution with ability to drive outcomes. - Experience working with offshore teams / multiple local operations hubs. - Basic SQL querying. - Competency in LLM / transformer models, and / or ML for robotics domain experience. - A greater focus on using your subject matter expertise for results analysis and direct customer consultation in the development of new and improved. solutions. - Self-motivated with basic skills in task planning and time management. In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: - Health, dental, vision, life, disability insurance - Retirement Benefits: 401(k) with company match - Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment - Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) - Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks - Baby Bonding Leave: 18 weeks - Holidays: 13 paid days per year This is a remote position. (Remote jobs only - Please note that Waymo may not be able to employ remotely in all locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.)) The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $130,000 - $160,000 USD
Senior Software Engineer, Mapping Data & Eval
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Roadgraph team builds the intelligent platform and automated pipelines that create, validate, and scale the high-definition geo knowledge base powering the Waymo Driver. We combine applied machine learning, computer vision, statistical evaluation, and large-scale distributed systems to solve one of the most foundational and exciting challenges in autonomous driving. High-definition mapping is a foundational pillar enabling the Waymo Driver to navigate safely, smoothly, and reliably. To rapidly expand commercial autonomous ride-hailing to new cities and continents, we must scale our automated mapping pipelines. This role sits at the center of that mission—building the applied ML models, evaluation engines, and large-scale data infrastructure that transform real-world sensor streams into the world's most precise and reliable spatial knowledge base. We work closely with onboard engineers to solve problems in an end to end fashion. You will be working on all aspects of the modeling life cycle (labeling, training, evaluation, inference), put your models to work, and measure impact on the overall system. You will: - Evaluate and launch machine learning models that automatically generate map from raw data. - Work with onboard teams to evolve Waymo’s mapping format to make it more automation friendly. - Apply statistical analysis to validate large-scale changes. - Build backend infrastructure for storing and processing many forms of map data. - Scale our systems to support mapping the whole world. You have: - B.S. in Computer Science or a similar technical field, or equivalent practical experience. - Hands-on experience with statistical analysis, experiment design, and quantitative evaluation of ML models or data pipelines. - Experience building scalable data processing pipelines using distributed frameworks like Google Data Flow or Apache Beam. - Demonstrated ability to take ownership of complex technical problems end-to-end and deliver measurable results in a collaborative team environment. - A passion for good software engineering. We prefer: - Master’s or Ph.D. in Computer Science, Machine Learning, Robotics, Computer Vision, or a related quantitative field. - Experience with high-performance computing, C++ optimization, and large-scale distributed systems architecture. - Domain familiarity with autonomous vehicles, robotics, high-definition (HD) mapping or GIS/spatial databases. LI-Hybrid The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000 - $263,000 USD
Senior ML Compiler Engineer, Compute
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle’s software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms. This role follows a hybrid work schedule and you will report to a Software Engineering Manager. You will: - Leverage agentic AI to accelerate analysis, planning and implementation of production software improvements - Analyze the performance characteristics of code generated by our production grade compiler, and design and implement optimizations to improve that performance - Design and implement compiler support for novel features of our high-performance architecture - Work with hardware architects to understand and influence the development of our unique neural network inference platform through hardware/software codesign - Work with model developers to tune their neural networks for better inference efficiency and accuracy You have: - BS degree in Computer Science/Electrical Engineering or equivalent experience and 5+ years of industry experience OR - MS degree in Computer Science/Electrical Engineering and 3+ years of industry experience - PhD degree in Computer Science/Electrical Engineering and 1+ years of industry experience - 3+ years experience working on compilers for parallel architectures - 1+ years experience working with ML inference or linear algebra computation - C++ programming skills, including leveraging agentic AI acceleration We prefer: - Python programming experience - Experience with compilers for neural networks, especially MLIR-based - Knowledge of computer architectures used for neural network inference, and neural network performance characteristics - Knowledge of the principles behind popular machine learning and neural network algorithms and applications The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000 - $263,000 USD
Senior Machine Learning Engineer, Vehicle Interact...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Role overview: Autonomy MLE role focused on bridging perception and planning to develop and release robust learned driving policies. The primary objective of this role is to train, evaluate, and transition production-ready decision-making models into real-world autonomous navigation systems. In this hybrid role, you will report to the Technical Lead Manager. You will: - Develop, evaluate, and release learned driving policies for complex navigation and yielding scenarios. - Work cross-functionally at the intersection of perception and planning, translating multi-modal perception outputs into robust behavioral actions. - Deploy learned models into closed-loop simulation environments, benchmark against strict safety metrics, and drive the transition of these models into production releases. - Advance the transition from rule-based heuristics to scalable, data-driven learned policies. You have: - 2–5+ years experience training and releasing ML models in autonomous driving, robotics, or complex spatial AI. - Hands-on experience working across both perception and planning stacks. Proficiency in learned driving policies (RL / imitation learning), PyTorch / JAX, closed-loop simulator evaluation, and a track record of releasing models to production. - Familiarity with Vision-Language-Action (VLA) models and World Models is a strong plus - Experience using foundation models and AI tools for scenario generation, evaluation analysis, and rapid experimentation. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000 - $263,000 USD
Senior Machine Learning Engineer, Maneuvering Tech
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Driver Refinement and Validation’s (DRV) mission is to build upon the high-quality ML Driver developed by Driver Intelligence, refining its performance to improve autonomous driving in specific, complex real-world contexts and problem areas (e.g., Ride-Hailing contexts). It aims to ensure that the Waymo Driver always computes safe, compliant, comfortable, and useful plans. As an Engineer in DRV, you will bridge the gap between cutting-edge machine learning and real-world vehicle performance, engineering the validation and onboard systems that ensure the autonomous vehicle reliably executes intelligent and predictable maneuvers. You will: - Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo’s business - Fine-tune, adapt, and benchmark state-of-the-art generative models to improve autonomous vehicle perception, motion prediction, and trajectory planning - Write high-quality, scalable, and thoroughly tested code to bring cutting-edge ML into production - Partner with world-class engineers and product managers to deliver safe and smooth autonomous vehicle behaviors You have: - MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience - 5+ years of industry experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments - Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities - Expertise with modern deep learning frameworks, such as JAX or PyTorch We prefer: - Experience in deep learning, reinforcement learning, and ML systems - Domain expertise in solving prediction, behaviors, motion planning, or related robotics problems - ML post-training experience - Prior industry experience (e.g. internships) in applied ML or software development - Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP) The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000 - $263,000 USD
Machine Learning Engineer, Prediction & Planning
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver’s behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently. In this hybrid role, you will report to a manager on our PrePlan team. Team matching happens after you've completed your onsite interviews. You will: - Develop the next-generation ML-powered prediction and planning system to enhance the performance and capabilities of the ML driver and support the rapid scaling of Waymo’s business. - Frame open-ended, real-world challenges as well-defined ML problems; research, develop, and apply cutting-edge ML techniques, including foundation models and reinforcement learning, for the planning and prediction tasks of autonomous vehicles. - Collaborate with world-class researchers, engineers and product owners to create safe, smooth planning behaviors for all road users and to meet product requirements. - Develop and evaluate large models, and integrate them into Waymo’s production planning software for real-world applications through close partnership with the Planner and Research teams. You have: - BS in Computer Science, ML, Robotics, similar technical field of study - 2+ years of experience in Machine Learning modeling and/or Autonomous Vehicles - Demonstrated contributions to the ML community through publications, open-source projects, or significant industry impact - Hands-on experience with modern deep learning libraries (eg: TensorFlow, JAX, Pytorch) - Proficient programming skills (eg: Python, C/C++) - Strong analytical and debugging skills We prefer: - MS or PhD in Computer Science, Machine Learning, Robotics, or a related field - Publications in top-tier conferences such as ICML, NeurIPS, CVPR, ICCV, ECCV, ICLR, IROS, CoRL, ACL, or EMNLP - General software engineering experience solving motion planning or related robotics problems - Experience applying or evaluating ML-based systems in production environments - Experience with performance optimization of deep models, including with respect to specific hardware architectures LI-Hybrid The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $175,000 - $215,000 USD
Machine Learning Engineer, Maneuvering Tech
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Driver Refinement and Validation’s (DRV) mission is to build upon the high-quality ML Driver developed by Driver Intelligence, refining its performance to improve autonomous driving in specific, complex real-world contexts and problem areas (e.g., Ride-Hailing contexts). It aims to ensure that the Waymo Driver always computes safe, compliant, comfortable, and useful plans. As an Engineer in DRV, you will bridge the gap between cutting-edge machine learning and real-world vehicle performance, engineering the validation and onboard systems that ensure the autonomous vehicle reliably executes intelligent and predictable maneuvers. You will: - Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo’s business - Fine-tune, adapt, and benchmark state-of-the-art generative models to improve autonomous vehicle perception, motion prediction, and trajectory planning - Write high-quality, scalable, and thoroughly tested code to bring cutting-edge ML into production - Partner with world-class engineers and product managers to deliver safe and smooth autonomous vehicle behaviors You have: - MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience - 3+ years of industry experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments - Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities - Expertise with modern deep learning frameworks, such as JAX or PyTorch We prefer: - Experience in deep learning, reinforcement learning, and ML systems - Domain expertise in solving prediction, behaviors, motion planning, or related robotics problems - ML post-training experience - Prior industry experience (e.g. internships) in applied ML or software development - Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP) The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $175,000 - $215,000 USD
2027 Summer Intern, PhD, Machine Learning Research...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. The subteam for this role will be: The Predictive Planning team (PrePlan) develops and deploys state of the art machine learning solutions that predicts the future state of the world and plans the Waymo Driver's Behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and perform at deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently. Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! You will: - Research, implement, and evaluate state-of-the-art generative models for planning and predictions using JAX - Conduct machine learning models experiments - Produce high-quality, thoroughly tested code - Collaborate with research, product, and engineering teams to introduce new research concepts You have: - Currently pursuing a PhD degree in Computer Science, Machine Learning, Robotics, or related field - Experience with deep learning, or reinforcement learning - Hands-on experience with modern deep learning libraries (eg: TensorFlow, JAX, Pytorch) with basic programming skills (eg: Python, C/C++) - Strong analytical and debugging skills We prefer: - Publications in top-tier conferences such as: ICML, NeurIPS, CVPR, ICCV, ECCV, ICLR, IROS, CoRL, ACL, or EMNLP - Prior software development or research industry experience (including internships) General Perks - Competitive compensation packages with a housing/relocation bonus (if applicable) - Medical, dental, and vision insurance - Fun intern events and networking opportunities Onsite Perks - Free breakfast, lunch, dinner, and snacks - Free access to Google shuttles - Onsite gym Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $85 - $85 USD
2027 Summer Intern, Perception - Evaluation
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware. Waymo interns work with leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skillset. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! This internship will be based on-site at our headquarters in Mountain View, CA. You will: - Improve signal quality in large scale perception evaluation workflows using generative AI (LLM/VLM) - Expand the capabilities of discovery evaluation system to cover a broader range of perception signals - Contribute to design and development of frameworks and methods for evaluating multi-task perception models - Collaborate with ML and infra engineers to integrate new signals to end-to-end model launch evaluation - Evaluate the impact of improvements on evaluation quality, focusing on precision, recall, and reliability You have: - Proficiency with coding in Python or C++ and navigating large codebases - Experience with building and/or evaluating machine learning models - Experience with data analysis and statistical evaluation - Enrolled in a Masters or PhD program in Computer Science, Robotics, or a similar technical field of study We prefer: - Multi-year C++ experience with contributions to large code bases or open source projects - Familiarity with perception models, in particular with object generation and semantics tasks - Experience in utilizing AI-powered workflows for data analysis or model evaluation - Experience in applying machine learning concepts and evaluation methodologies - Proven experience in building data and evaluation pipelines and processing large-scale datasets Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly Masters Pay $70 - $70 USD The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $85 - $85 USD
AI Sales Engineer
Vectara provides an Agent Platform that allows organizations to rapidly create AI applications that are grounded in the context from their data and knowledge. Our end-to-end platform provides critical capabilities required for enterprise adoption: high accuracy even with incredibly complex data, powerful agent harness, comprehensive observability, and the ability to run in any environment (cloud, VPC, on-premise). We build AI for doing. We are passionate about helping users take advantage of breakthroughs in applied AI to solve problems and get stuff done. Our team is a group of unquestionable all-stars in their respective fields of computer science and business. Come join us in this mission. Role Overview: Vectara is looking for an experienced Sales Engineer to join us. You will be connecting customers with the magic of our product, aligning our capabilities to the pain points and business opportunities they are attacking. You will remain the trusted technical point of contact throughout the customer's journey with our product. You will work as an integral part of our Sales and Customer Success motions, and you will work hand-in-hand with our Professional Services team. This will include assisting them as they first learn about the product and conduct their evaluation, then helping as they build their first production application, then providing assistance and guidance once they have launched. By doing so you will play an integral part in delivering sales and customer satisfaction outcomes for our business. To do this well you will maintain a strong relationship with our Product, Engineering, and Machine Learning teams, so you can effectively respond to customer needs while ensuring that what we build meets the requirements of the market. You will be the technical face of the company and build relationships with the technical leaders within the customers you serve. In this way you will positively influence your customers and help them successfully navigate their way through the AI era. If you enjoy being a technical thought leader who provokes fresh ideas on what is possible, provides clear explanations for how to incorporate AI into impactful products, and has a very strong customer-first orientation, then we should talk. Key Responsibilities: While accomplishing the above big picture outcomes, your day-to-day tasks will include the following: - Providing technical product expertise - Conducting demos, including custom-built ones when needed - Helping with POCs - Assisting customers with architecture, design, and development - Scoping and planning PS projects - Conducting evaluations and performance tuning of retrieval and agentic pipelines to ensure applications meet rigorous enterprise requirements - Responding persuasively to functional and technical elements of RFIs/RFPs - Conducting regular check-in meetings with customers to update them on new features and identify opportunities for expanded usage - Communicating relevant feedback to internal teams to improve our product and processes Qualifications: - 5+ years of Sales Engineering experience, supporting the GTM motion of companies in one of the following spaces: AI, ML, search, analytics, data engineering - Experience selling technical products to AI, Data, or IT organizations within large enterprises - 2+ years of Professional Services or internal development experience, working in large enterprises to design and develop applications - Experience with agentic AI development, spanning the context layer to the agent harness - skills, tools, guardrails, etc. - Development experience with Python and/or Java - Experience developing apps that heavily consume REST services - Understanding of architectural principles for cloud-based platforms, including SaaS, VPC deployments, multi-tenancy, and automation - Understanding of architectural principles for on premise systems, including hardware, compute (especially GPUs), virtualization (especially k8s), and networking - Strong communication, interpersonal and collaboration skills - Compelling storyteller, with experience building product narratives and pitches - Ability to communicate complex technology concepts crisply and simply - Should be available to travel to visit your accounts up to 20% of the time - Bachelor’s degree in Computer Science, Computer Engineering or an equivalent field of study; MS a plus but not required - Location: US West Required, Bay Area preferred Salary is just one component of Vectara’s employee compensation. Our full-time employees are also equity owners in the company, which although not an immediate cash component, can have positive impacts on long-term total compensation for each participating employee. We would be remiss if we didn’t highlight and celebrate our focus on engaging many of our employees in being economic co-owners of the business. Vectara welcomes all. We value the collective wisdom of people from different backgrounds, experiences, abilities and perspectives. We never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Vectara has a positive and supportive culture—we look for people who are inventive and work to be a little better every single day. We seek to be smart, humble, hardworking and, above all, curious. Perks and Benefits: 100% paid Medical, Dental, Vision for employees. Option of Health Savings Account (HSA) or Flexible Savings Account (FSA). Generous paid time off (PTO) plus paid sick time and holidays. Professional development and training opportunities. A supportive, caring company culture that treats each team member with respect and empathy.
Senior Product Marketing Manager
About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . About the Role We’re looking for a Senior Product Marketing Manager to lead product marketing for Turing’s Frontier AI business. Our customers are building frontier AI models that rely on Turing’s high-quality datasets, reinforcement learning environments, benchmarks, and expert network to train & improve their models. This role is ideal for someone who thrives in a fast-moving environment and is excited to shape the narrative around our products and create compelling content for AI researchers, including technical blogs, demos, and customer-facing presentations. Who You Are You’re intellectually curious and enjoy learning how AI models are trained and improved. You ask thoughtful questions, synthesize complex information quickly, and can turn technical details into messaging that resonates with customers. You enjoy collaborating with AI researchers and other technical stakeholders. You combine strategic thinking with a bias for execution and are comfortable taking ownership in a fast-moving, collaborative environment. Most importantly, you’re excited by the opportunity to help accelerate frontier AI by enabling better data, better evaluations, and better model performance. What You’ll Do Develop Positioning and Messaging - Develop differentiated positioning and messaging for our datasets, benchmarks, research, and reinforcement learning environments. - Translate complex technical capabilities into clear, compelling value propositions for AI researchers. - Partner closely with the Research team to ensure our messaging accurately reflects Turing’s capabilities and differentiation. Lead Product Launches - Lead go-to-market execution for new products and capabilities. - Coordinate cross-functional launch plans and ensure teams are aligned on messaging, enablement, and customer communications. - Create launch materials, including product pages, technical blogs, presentations, customer stories, demos, and sales enablement content. Be the Voice of the Customer - Develop a deep understanding of frontier AI labs and their technical decision-makers. - Conduct customer interviews, market research, and competitive analysis to identify emerging trends and customer needs. - Bring customer and market insights back to Research teams to help inform roadmap and positioning decisions. Enable Our Go-to-Market Teams - Develop sales enablement materials that help teams communicate product value to technical buyers. - Create competitive intelligence and battle cards. - Partner with Sales and Customer Success to improve product adoption and customer engagement. Qualifications Required - 5+ years of experience in Product Marketing, Technical Marketing, or a related go-to-market role. - Bachelor's in Marketing, Computer Science, Engineering, or related field — or equivalent experience - Experience marketing highly technical products, such as AI/ML platforms, developer tools, cloud infrastructure, or data platforms. - Demonstrated ability to understand complex technical concepts and communicate them clearly to technical audiences. - Experience leading cross-functional product launches from planning through execution. - Excellent written and verbal communication skills, with the ability to create compelling technical and customer-facing content. - Strong customer research, competitive analysis, and market insight skills. Preferred - Experience with AI, machine learning, data infrastructure, developer platforms, or foundation model ecosystems. - Familiarity with concepts such as: - Foundation models - Model evaluations - Reinforcement learning (RLHF, RLVR) - Synthetic data - Human-in-the-loop systems - Multimodal AI - LLM benchmarking - Data pipelines - Experience marketing to AI researchers, ML engineers, developers, or other technical audiences. - Bachelor’s degree in Marketing, Computer Science, Engineering, or a related field, or equivalent practical experience. What Success Looks Like Within your first year, you’ll: - Develop clear, differentiated messaging across key product areas. - Successfully launch new products and capabilities that drive customer engagement and adoption. - Deepen our understanding of customer needs through ongoing market and customer research. - Help strengthen our reputation as a trusted and a research-forward partner to frontier AI labs. Compensation: $159,000 to $205,000 base + equity LI-VC1 Values - We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. - We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection - We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing - Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. - Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. - Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. - Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. - Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .
Software Engineer, Evaluation Platform / Infra
ABOUT THINKING MACHINES The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it. ABOUT THE ROLE Evaluation is one of the most important pillars of building frontier AI systems. It guides research direction, powers experimentation, and helps us understand whether changes to data and training are improving the capabilities and behaviors we care about. To support this work, researchers need a powerful, self-serve platform that makes it easy to author evaluations, run them or reproduce them reliably at scale, and extract insight from the results. The platform must support both standardized external benchmarks and fast-moving internal evaluations, many kinds of tasks and graders, and inspection from aggregate metrics down to individual model trajectories. In this role, you will design and build this platform end to end. You will work across Python frameworks, data pipelines, APIs, and user-facing applications, and collaborate closely with pre-training, post-training, and applied teams to improve how we evaluate models and turn results into research decisions. WHAT YOU'LL DO - Design, build, and maintain the platform for authoring, running, tracking, and analyzing model evaluations that are critical in day to day work and model releases. - Work across evaluation libraries, distributed backend systems, data pipelines, APIs, and user-facing applications to deliver capabilities end to end. - Build flexible abstractions for evaluation tasks, environments, graders, datasets, and model outputs without constraining fast-moving research. - Make evaluation results reproducible and trustworthy through versioning, provenance, observability, failure recovery, and robust quality controls. - Partner directly with researchers to identify bottlenecks and turn bespoke workflows into self-serve systems that work across teams. - Work with Research Tooling, the engineering team behind Thinking Machines’ internal research platform. SKILLS AND QUALIFICATIONS MINIMUM QUALIFICATIONS - A bachelor’s degree, or equivalent practical experience, in computer science, engineering, machine learning, or a related field. - Two years of post-grad work experience as a software engineer or ML engineer, exclusive of internships. - Hands-on experience building or maintaining evaluations, benchmarks, graders, or model-quality systems for large language or multimodal models. - Strong software engineering fundamentals and experience building reliable, maintainable systems. - Proficiency in at least one backend programming language; we primarily use Python and Rust. We use React and Typescript on the frontend. - Experience with databases, data pipelines, distributed systems, or other data-intensive infrastructure. - Comfort working across the stack and owning projects from initial problem discovery through deployment and operation. - Experience collaborating with cross-functional partners and subject-matter experts. PREFERRED QUALIFICATIONS We encourage you to apply even if you meet only some of these: - A track record of building frameworks, SDKs, or developer tools with thoughtful abstractions and a strong user experience. - Experience with distributed job execution, workflow orchestration, sandboxed environments, or large-scale data processing. - Experience building polished, intuitive interfaces for inspecting complex data, comparing experiments, or debugging model behavior. - Familiarity with large language or multimodal model evaluation, including model-based grading, human evaluation, or synthetic data. - Experience working closely with researchers to understand their workflows and turn rapidly evolving needs into durable systems. - Experience at a startup or on a small team, building technically complex products end to end. LOGISTICS - Location: This role is based in San Francisco, California. - Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $350,000 USD. - Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together. - Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
Research, Coding Agents
ABOUT THINKING MACHINES The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it. ABOUT THE ROLE - The Coding Agents team makes our models world-class at agentic coding — writing, debugging, and reasoning about code across long-horizon, multi-turn tasks. - You'll join a small, high-leverage team responsible for the recipes, data, and infrastructure behind coding capability gains in every model release. - The team owns the full coding post-training stack: synthetic and human data generation, RL environments and sandboxes, reward and grading design, and large-scale training runs. - This is a research role with real ownership — you'll shape technical direction, not just execute against a spec. Note: This is an "evergreen role" that we keep open on an on-going basis to express interest in this research area. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role. WHAT YOU’LL DO - Design and run RL training jobs targeting agentic coding capabilities, iterating on recipes and data. - Build and improve the sandboxed coding environments and reward signals that models are trained and evaluated against. - Generate and curate high-quality synthetic coding data, and build scalable, general-purpose data pipelines. - Design evals that measure real-world coding usefulness, and train models against them to deliver concrete improvements in day-to-day usability. - Debug and analyze large RL runs to catch confounders, reward hacking, and other RL failure modes. - Collaborate closely with infra, evals, and other post-training teams on shared data, joint training runs, and usability improvements — and ship the results into model releases. SKILLS AND QUALIFICATIONS Minimum qualifications: - Strong engineering skills, ability to contribute code and debug in complex codebases. - Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX). Comfortable with debugging distributed training and writing code that scales. - Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding. - Clarity in communication, an ability to explain complex technical concepts in writing. Preferred qualifications — we encourage you to apply even if you don’t meet all preferred qualifications, but at least some: - Experience building synthetic data pipelines and systems that were adopted by others on your team and remain in use today. - Experience owning the end-to-end cycle of identifying gaps in model usability and closing them through custom evaluations and training data. - Experience making large-scale agentic RL infrastructure reliable given the long tail of failures that surface at scale. - Experience improving the coding capabilities of a frontier model. - PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience. LOGISTICS - Location: This role is based in San Francisco, California. - Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD. - Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together. - Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
Machine Learning Scientist
ABOUT SUNO We're building the world's first creative entertainment platform, where the entire world can feel the joy and fulfillment of making music. Music is for everyone: Our users include everyone from grandmothers creating songs for their loved ones, to Grammy winners using Suno Studio, our power tool, to make the most popular hits in the world. Building the future of entertainment requires ambition. The pace is fast, the problems are hard, and the work demands ownership and intensity. For the right people, it’s incredibly rewarding: a chance to shape a new medium, work with a small team that cares deeply about quality, make music, drink too much coffee, and build something that millions of people use to express themselves in ways that were never before possible. Suno is the fastest growing consumer entertainment company and the leader in AI music. We are backed by leading investors including Bond Capital, Menlo Ventures, Lightspeed Venture Partners, IVP, Forerunner, Union Square Ventures, Alkeon, Quiet, Matrix Partners, Schroders Capital and, NVentures (venture arm of NVIDIA). ABOUT THE ROLE We’re looking for early members of our research team. You’ll work closely with the founding team and have ownership of a wide variety of technical decisions on how we build and deploy our state of the art ML models trained with an H100/scientist ratio of >100x. Check out our Suno version of the job here: https://suno.com/s/YaZAme1qvoqFJOi1 WHAT YOU’LL NEED - 5+ years experience training state of the art models with distributed pytorch - Intimate familiarity of the entire stack of data engineering, designing, training and evaluating machine learning models - Track record showing independent ownership of entire research projects from start to finish - Extensive experience training large generative models from scratch (LLMs or diffusion models) - A love of music (listening, exploring, making) is a huge plus - Bachelor's degree or equivalent required. Additional Notes: Applicants must be eligible to work in the US. COMPENSATION The annual salary range for this role is $207,454 – $394,800 + target equity + benefits (including medical, dental, vision, and 401k) PERKS & BENEFITS FOR FULL-TIME EMPLOYEES - Company Equity Package - 401(k) with 3% Employer Match & Roth 401(k) - Medical, Dental, & Vision Insurance (PPO w/ HSA & FSA options) - 11 Paid Holidays + Unlimited PTO & Sick Time - 16 Weeks of Paid Parental Leave - Creative Education Stipend - Generous Commuter Allowance - In-Office Lunch (5 days per week) Suno is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the Massachusetts Fair Chance in Employment Act, NYC Fair Chance Act, LA City Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.
AI Applications Engineer (Glen Cove, NY)
About Standard Bots Standard Bots is building the next generation of industrial robots -- hardware that's powerful, affordable, and designed to scale. We're the largest U.S. industrial robotics company by robots shipped, and our robots are showing up on factory floors everywhere from independent machine shops to NASA and Lockheed Martin. Note: This role requires up to 50% domestic travel. That number goes down as we grow the team, but right now you're in the field -- a lot. If that's not for you, this probably isn't the right fit. Also note: If you're looking for a role where you train models and push code, this isn't it. This is a mechanical + electrical + software trifecta that happens to use AI as a tool. The factory floor is your office. The Role The AI Applications Engineer sits at the intersection of robotics, AI, and hands-on field work. You're not a pure software engineer and you're not a pure hardware engineer -- you're the person who can look at a manufacturing challenge, figure out how computer vision or a language model makes the robot smarter, and then actually build and deploy the solution. You'll work closely with the sales, software and applications engineering teams to scope AI-enabled solutions, build proofs of concept in our shop, and travel to customer sites to install and commission them. You'll own your projects end-to-end -- from initial design through field deployment and customer training. This is a builder's role. Tinkerers and people who get bored at a desk are strongly encouraged to apply. What You'll Do AI Solution Design & POC Development - Work with customers and the sales team to identify where AI -- computer vision, object detection, visual language models -- creates real leverage in their production process - Design and build proofs of concept that validate the solution before anyone signs anything - Develop documentation, sample code, and integration guides that help customers and internal teams replicate and scale what you've built Field Deployment & Integration - Travel to customer sites to install, configure, and commission AI-enabled robotic cells - Own the full integration: camera placement and calibration, model deployment, I/O configuration, testing, and sign-off - Troubleshoot on-site when things don't go as planned -- you stay until it works Customer Training & Support - Train customer operators and engineers on the AI capabilities of their Standard Bots deployment - Be a trusted technical resource post-install as customers push the system into new applications - Feed real-world deployment learnings back to our engineering and product teams Internal Collaboration - Work with the broader applications and engineering teams on new feature testing, peripheral integrations, and platform expansion - Help build the internal knowledge base on AI-enabled applications -- what works, what doesn't, and why What We're Looking For Core Skills (Must have all or most) - Robot programming proficiency or adjacent software experience -- if you can write Python without an AI agent, you can probably program a robot having never touched one before - Prior robotics knowledge -- anything from high school robotics to professional manipulation experience; we care that you've actually worked with robots, not just read about them - Surface-level fluency in ML models and techniques -- you can have a real conversation about convolutional neural networks, object detection, and visual language models without Googling the definitions mid-sentence - Technical proficiency in an engineering environment -- you write documentation, manage your own projects, work well with a team, and don't need someone watching over your shoulder - Willingness to travel -- up to 50% domestically right now; that number will come down as we grow Specializations (Must have at least one) - Mechanical Design -- pneumatics, camera mounts, end-of-arm tooling for manipulators; bonus points if you've designed a gripper - Electrical Design -- custom board fabrication, general electrical knowledge for wiring relays and solenoids in automation environments - Machine Vision -- you know which cameras and lenses to use for a given application and why; you've actually deployed a vision system, not just selected one on paper Nice to Have - Experience with collaborative robots (UR, Fanuc, KUKA, ABB, or similar) - Hands-on work with vision systems in a production or lab environment (Cognex, Basler, FLIR, or similar) - Familiarity with ROS or other robotics middleware - Background in a manufacturing or industrial automation environment - Experience at a startup -- you know what it means to build something from scratch with limited resources Compensation and Benefits The salary range for this role is $120,000 to $150,000, depending on experience. We are open to a variety of seniority levels for this role and will build compensation packages that are commensurate with seniority and skill level. Base salary is just one part of the overall compensation at Standard Bots. All Full-Time Employees are eligible for Employee Stock Options. We also offer a package of benefits including paid time off, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees.
Senior Backend / AI Systems Engineer
Spellbook is the most comprehensive AI copilot for transactional lawyers. It works directly inside Microsoft Word to help legal teams draft, review, and negotiate contracts up to 10x faster and with greater precision. Today, more than 4,000 law firms, in-house teams, and solo practitioners rely on Spellbook to simplify their workflows and eliminate the drudgery of everyday contract work. We are backed by leading investors including Khosla Ventures, Thomson Reuters Ventures, Inovia Capital, The LegalTech Fund, Bling Capital, and Moxxie Ventures. The company recently raised $50 million in Series B funding, led by Keith Rabois at Khosla Ventures, bringing its total funding to more than $80 million. *This is an existing vacancy ABOUT THE ROLE You’ll build the backend systems that power Spellbook’s product experiences, including both traditional software services and AI-driven workflows. This is a hands-on, high-ownership role for an engineer who cares about product outcomes and understands what requires scale vs what does not, and can turn ambiguity into robust systems that lawyers trust. THE TECH STACK Node.js, TypeScript, Express, tRPC, MongoDB, Docker, AWS, CDK, LLM providers (OpenAI, Anthropic, and others) RESPONSIBILITIES - Build and scale backend systems that support core product functionality across Spellbook (Reviews, Chat, Library, and more). - Design low-latency, high-reliability search, inference, and orchestration layers for AI features - Build and operate RAG retrieval at scale with production-grade performance optimization and permissions-correct data isolation. - Own core platform concerns for AI: rate limiting, retries, consistency, fallbacks, safe degradation - Partner closely with Product and Design to make good tradeoffs between latency, accuracy, UX, and reliability. - Use modern development workflows, including agent-assisted coding, to accelerate delivery while maintaining rigorous review, testing, and security standards. - Participate in on-call and incident response as needed, and improve feature reliability in the process QUALIFICATIONS - You have 5+ years of experience building backend systems in production. - You have strong fundamentals in backend engineering and distributed systems: APIs, data modeling, concurrency, queues, AI inference - You have strong NoSQL (ideally MongoDB) data modeling and performance tuning: schema design/denormalization tradeoffs, indexing strategy, query optimization, and profiling/diagnosing bottlenecks in production. - You can take an ambiguous, high-impact problem from “we should do something here” to a clear plan and shipped outcome. - You have strong communication skills. You can write and explain technical decisions clearly to engineers and non-engineers. - You are a self-starter and problem-solver motivated by curiosity and a desire to help others succeed, encouraged by continuous improvement. - You are pragmatic and understand that not everything we ship needs to scale, but know where to draw the line - You are a team player who is motivated to help Spellbook succeed. When things break you are eager and able to help fix them. You think of and implement ways to help and improve the work of the team as a whole. NICE TO HAVES - Experience building LLM-powered systems in production, including prompt iteration, tool/function calling, retrieval patterns, and agent orchestration. - Experience operating high-scale retrieval systems (vector + lexical search) and measuring/tuning retrieval quality and latency in production. - Experience building evaluation frameworks (quality metrics, dataset curation, regression testing). - Experience with AWS CDK and operating production services in AWS. We are only considering candidates in Ontario for this role. This role is not subject to Ontario's salary range disclosure requirement, as total compensation exceeds the threshold set out in the exemption. We're happy to discuss compensation details directly with candidates as the process progresses. WHY JOIN SPELLBOOK? - Embrace autonomy and accountability in a flexible work environment; we focus on outcomes and empower you to determine how to get the job done - Access our company-paid group benefits for you and your family, with $1,000 towards mental health support - Disconnect during our holiday closure and take advantage of our generous time off policies throughout the year - Enjoy monthly paid meals, an annual wellness allowance to support your well-being and parental leave top-ups as your family grows - Secure your stake in our success; you’ll receive competitive stock option grants as a pivotal early employee INCLUSIVE HIRING AT SPELLBOOK We are committed to creating an inclusive and supportive candidate experience. Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation. Spellbook is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law. We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category. Spellbook is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation. USE OF ARTIFICIAL INTELLIGENCE IN RECRUITMENT Spellbook uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process. This includes activities such as drafting job descriptions, generating interview questions, note-taking and recordings, and supporting sourcing and scheduling workflows. All candidate evaluations, interviews, and hiring decisions are made by members of the Spellbook team. While AI tools may assist with screening and assessment, they do not replace human judgment in selection decisions. Our use of AI is intended to streamline routine tasks, improve consistency, and enhance the overall candidate experience. We are committed to upholding principles of fairness, transparency, and accountability in all hiring activities. Spellbook regularly reviews its recruitment practices to mitigate bias and to ensure alignment with applicable laws and evolving best practices. OUR COMPENSATION PHILOSOPHY Spellbook uses industry benchmark data to establish compensation bands for all roles. The salary range listed for a position reflects the expected total wage range for the role—including base salary and on-target commissions, where applicable—and may span multiple career levels. Final compensation is determined during the interview process based on factors such as experience, skills, scope, and role level. In addition to base salary and applicable commissions, total rewards may include equity, health and wellness benefits, and other company programs. Full details will be shared during the interview process.
ML Data & Platform Engineer
We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do - Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models - Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale - Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production - Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency - Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly - Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference - Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need - Strong proficiency in Python and SQL, with a solid backend or data engineering foundation - Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider - Experience building data pipelines and ETL/ELT processes at scale, including web scraping or automated data collection - A solid understanding of the ML lifecycle, from data through to model training, evaluation, and serving - Experience with data quality practices (validation, cleaning, normalisation) and/or production-grade observability - Ability to design resilient, scalable architectures, and comfort operating and troubleshooting distributed systems - MLOps experience, for example model serving, experiment tracking, GPU/distributed training optimisation, or reproducible ML workflows - A self-starter mentality: comfortable identifying problems and driving fixes without needing detailed direction We encourage you to apply even if you do not feel you match all of the requirements exactly. The list of requirements is intended to show the kinds of experience and qualities we’re looking for, but it is not exhaustive. If you are interested in the role, the team, and our mission, we would love to consider your application. We are always open to conversations and look forward to hearing from you. Who we are: Speechmatics is the leading expert in Speech Intelligence, and uses AI and Machine Learning to unlock business value in human speech worldwide. We work with an amazing mix of global companies, and our technology can integrate into our customers stack irrespective of their industry or use case – making it the go-to solution to harness useful information from speech. Joining us means working with some of the smartest minds around the world, focused on cutting-edge projects and deploying the latest techniques to disrupt the market. We believe in putting people first; we’ll do all we can to help you develop your skills and give you the tools you need to thrive. Our Focus Fridays give you an undisturbed day of focus, offset with Together Tuesdays when we have our team meetings, so you've always got the right balance. We have structured a hybrid approach that includes 2-3 designated office days each week. This arrangement ensures that while we embrace the advantages of remote work, we also maintain the vital connection and synergy that only in-person interactions can foster. This is only the beginning; we’re looking for amazing people like you to continue our journey… What we can offer you: No matter what stage of your career you’re at - from paid internships and first-job opportunities through to management and senior positions - we’ll support you with the training and development needed to reach your career aspirations with us. There really is no shortage of opportunities here for you to get involved and collaborate with those around you to deliver your best work. We offer incredibly flexible working, regular company lunches, and birthday celebrations. But that’s not all. We’ve spoken to our teams to find out what they want. From Private Medical, and Dental for you and your family, through to global working opportunities, a generous holiday allowance and pension/401K matching, we want to make sure our employees and their families are looked after. Every employee will receive a working from home allowance for tech or home office equipment (on top of your choice of laptop and accessories of course). Our approach to parental leave is designed to support employees globally. While this varies by geo, we have support in place for parents (including adoption assistance and reproductive health services) to ensure they have the time and financial resources needed to care for their growing families. At Speechmatics, our mission is simple: Understand Every Voice out there. That's not just about our tech – it's the heart and soul of who we are. We welcome different experiences, viewpoints, and identities. For us, it’s not just the right thing to do; it’s our catalyst for sparking innovation and creativity. Our teams thrive in an environment that celebrates and supports everyone – no matter their gender, identity or expression, race, disability, age, sexual orientation, religion, belief, marital status, national origin, veteran status, pregnancy, or maternity status. But we don’t just open the door to diversity – we actively welcome it. Why? Because we believe every unique voice adds something special to our team, leading us to smarter solutions and a better workplace. So, come as you are and join our Speechling community. We’re building a place where every voice not only gets heard but is also respected and valued. For more information on us , please visit our website and follow Speechmatics on our social channels via Twitter , Facebook , LinkedIn , and YouTube. We rely on legitimate interest as a legal basis for processing personal information under the GDPR for purposes of recruitment and applications for employment. LI-Hybrid
Staff Product Manager - Data Products
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! The Role We're looking for our founding AI Data Product Manager to own Snorkel's Agentic Data and RL Environments roadmap. In this role, you'll lead the product strategy for a variety of data types (e.g. Agentic Coding, Computer Use). You will shape the roadmap for the datasets Snorkel invests in by understanding the market, incorporating frontier lab needs and collaborating with researchers at Snorkel and our academic partners. This role is highly cross-functional, sitting between Research, GTM and Operations. As a founding member for this role, you will be in charge of setting up the frameworks to build the roadmap, gather data from relevant sources, and share the roadmap with both internal and external stakeholders. What You'll Do - Own the "data as a product" roadmap for Snorkel's Agentic and RL Environment focus areas, working x-functionally with research, academic partners, and GTM to define the skills and capabilities for our datasets - Shape new "data" product areas and work with academic partners and research leaders to build Snorkel's competitive edge in the market - Collaborate cross-functionally to help shape the roadmap and data strategy and influence business strategy Minimum Qualifications - 4-6 years of experience shaping technical roadmaps and working with researchers as stakeholders - Comfort with ambiguity and working with multiple technical and non-technical stakeholders - Experience working in fast-paced environments, setting up 0→1 products - AI and ML fluency, especially related to Frontier Agentic Workflows and RL Environments - 8+ years in product management, including 3+ years at senior/staff level owning a roadmap end-to-end (or 6+ years with a PhD/research background in ML) - Demonstrated ownership of a technical product where data itself was the deliverable — datasets, benchmarks, evals, annotation pipelines, or labeled corpora sold or shipped to external consumers - Working fluency in modern LLM post-training: SFT, preference data (RLHF/RLAIF), RLVR, reward modeling, and how data composition affects model capability. Must be able to hold a substantive conversation with a research scientist without an interpreter - Familiarity with agentic systems and the current agentic eval landscape (e.g. SWE-bench-style coding evals, terminal/computer-use benchmarks, tool-use and long-horizon task evaluation) and an informed view on where they fall short - Track record building product frameworks from zero — prioritization models, roadmap artifacts, intake processes — in an environment with no existing playbook - Experience operating across research, GTM, and operations simultaneously, with evidence of driving decisions through influence rather than authority - Direct customer-facing experience with highly technical buyers; ability to run a discovery conversation with an ML researcher or post-training lead and convert it into a roadmap commitment - Quantitative rigor: can size a market, model unit economics of a data program (cost per trajectory/task/environment), and defend prioritization with numbers - Strong technical foundation — comfortable reading research papers, discussing training dynamics with scientists, and reasoning about data pipelines end-to-end. - Ability to write clearly for two audiences at once — internal research/ops and external frontier lab stakeholders - Excellent analytical instincts — able to define success metrics for products that live close to research, where outcomes are often indirect. Preferred Qualifications - Prior experience at an AI data/environments company or inside a frontier lab's data, post-training, or evals org - Has built or specified RL environments — sandboxed/containerized task environments, verifiable reward design, task generation, environment scaling and reproducibility - Direct experience with agentic coding or computer-use data specifically: trajectory collection, rubric design, verifier construction, failure-mode taxonomy - Hands-on technical ability — can write Python, query data, run a model, and prototype an eval without engineering support - Experience selling or delivering into frontier labs, with an existing network among post-training, evals, or data acquisition leads - Experience structuring academic or research partnerships, including co-development of datasets or benchmarks - Published research, open-source datasets/benchmarks, or public writing that establishes credibility with the research community - Experience with pricing and packaging for bespoke or semi-standardized data contracts, and the tension between custom deals and repeatable product - Competitive intelligence muscle — has run structured win/loss or market mapping in a fast-moving, opaque market - Prior founding-PM or 0→1 experience at a company between Series B and IPO - Domain depth in one or more target verticals for agentic data (software engineering, enterprise workflows/CRM-ERP automation, finance, healthcare) - Experience with human-in-the-loop data pipelines, annotation quality systems, or synthetic data generation at scale. - Track record of leading large, cross-team initiatives without formal authority. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $260,000 - $300,000 USD Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Software Engineer, Agent - Healthcare
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. ABOUT THE HEALTHCARE TEAM - Our healthcare agents already reach over 50% of U.S. families. We partner with leading health plans, providers, and healthcare platforms to deliver AI agents that handle some of the most sensitive and high stakes conversations in any industry. From helping members understand their benefits to resolving billing questions with empathy, our healthcare agents are transforming how patients and policyholders interact with the healthcare system. - Our healthcare customers include major health insurance networks, nonprofit providers, multi-site primary and urgent care practices, healthcare diagnostics companies, and healthcare financial platforms. - Join us to transform the patient experience across the healthcare system—and help build technology that makes care more accessible, more human and more affordable for everyone. WHAT YOU'LL DO - Design and deliver production-grade AI agents for healthcare: You'll build and ship highly performant, reliable, and empathetic AI agents that handle sensitive patient and member interactions. These agents help people understand their coverage, find providers, schedule appointments, navigate billing, and more—all while maintaining strict HIPAA compliance and the trust that healthcare demands. - Drive the Agent Development Life Cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments serving healthcare payers, providers, and platforms. - Partner with healthcare leaders: You'll work directly with executives and technical teams at health plans, provider networks, and healthcare technology companies to understand their most pressing challenges - from managing high call volumes to reducing administrative burden and building AI agents that transform how they operate at scale. - Navigate healthcare complexity: You’ll develop deep expertise in healthcare systems and workflows, including integrations across EHR and patient access platforms, payer and provider operations, and common healthcare data and interoperability standards. You’ll become fluent in the nuances of benefits and eligibility, claims and billing, scheduling and intake, and translate that understanding into exceptional, trustworthy AI experiences. - Build the future of the platform: Your direct work with healthcare customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development in healthcare. EXAMPLE PROJECTS These are examples of projects our healthcare team has worked on: - Build AI agents for major health insurance networks that handle detailed questions such as, "What's my co-pay for a primary care visit?" and "How many physical therapy sessions do I have left?" - Develop voice and chat agents for healthcare providers that help members find in-network specialists, check availability, and locate providers based on specialty or location; - Create AI agents for multi-site primary and urgent care providers that manage appointments and answer common questions across 30+ clinics; - Build agents that replace lengthy paper intake forms with conversational experiences, boosting pre-visit intake conversion rates; - Develop AI agents for healthcare financial platforms that help patients understand billing, payment status, explanations of benefits, and financial assistance eligibility - all while maintaining HIPAA compliance and strong PHI/data privacy safeguards. - Experiment with the latest voice models and integrate them at scale for healthcare enterprises requiring secure, compliant phone interactions; WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems. - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments. - A builder and tinkerer's mindset with high agency - you find creative ways to overcome obstacles and ship. - Comfort working directly with customers to understand their needs and solve real-world problems. - Excellent communication skills—clear, direct, and persuasive across technical and non-technical audiences. - Genuine interest in healthcare and improving patient/member experiences. EVEN BETTER... - Experience in healthcare technology, health IT or working with healthcare organizations - Familiarity with healthcare systems: Major EHR ecosystems (e.g., Epic, Cerner/Oracle Health, athenahealth); X12 EDI transactions and clearinghouse workflows; scheduling/patient access, practice management, and contact center platforms. - Understanding of healthcare compliance requirements (HIPAA, PHI handling and healthcare data privacy). - Experience building or deploying AI/LLM systems in production. - Have been a founder or founding engineer—you know what it means to balance craft, ownership, and speed. - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering. - Prior experience with React, TypeScript, and/or Go. - Previous roles where you interfaced with customers or led technical projects with external stakeholders. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer Intern, Agent (Summer 2027)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. As a Software Engineer Intern, Agent, you'll work directly on production AI agents for Sierra's customers. You'll gain hands-on experience contributing to the design and development of AI agents, shipping features, and learning from real-world use cases at scale. If you're hungry to shape and learn from the most important technological wave in history, come build at Sierra. WHAT YOU'LL BRING - Pursuing a bachelor's or master's degree in computer science or a related field - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER - Experience building or deploying AI/LLM systems in production - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go INTERN QUALIFICATIONS - The intern program is open to students graduating December 2027 - June 2028 - Note: The full benefits listed below are available only to full-time employees. Interns are eligible for a monthly stipend for health insurance, daily lunch, and, of course, free alphorn lessons. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Staff Engineer, Data Platform (R5659)
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: We are looking for a Staff Data Platform Engineer to help define and build the data foundation of the AI Factory. The Data Platform provides a unifying, knowledge-graph-centered API layer for human and agentic workflows. It connects configurations, requirements, software versions, test executions, files, signals, training data, and results through stable identities and typed relationships. It also provides consistent access to the storage and compute systems behind those data products. This is a hands-on technical leadership role. You will design platform architecture, implement production software, evaluate storage and compute technologies, establish data-modeling patterns, and work directly with teams collecting and consuming mission-critical data. Success requires balancing developer productivity, semantic clarity, operational reliability, system performance, portability, and long-term maintainability. What you'll do: Develop a unifying Graph API: Lead the architecture and implementation of the knowledge graph and multi-modal API layer that serves as the backbone for human, service, and agentic workflows. Own DataOps infrastructure: Research, optimize, and maintain the storage, indexing, query, ingestion, and compute infrastructure used throughout the data lifecycle. Establish best-practices: Establish durable, best-practice patterns for schema modeling, relationships, lineage, and schema evolution. Turbocharge agentic data access: Build APIs that enable agents to retrieve structured, connected, and explainable context rather than relying only on keyword or vector similarity. Develop reference architectures: Establish recommended storage and compute profiles, deployment patterns, benchmarks, and operational guidance for both internal and customer-managed infrastructure. Advise downstream teams: Partner directly with autonomy, ML, test, infrastructure, product, and customer-facing teams to turn real workflows into reusable platform capabilities from modeling to integrations. Build first-party integrations: Deliver integrations that make important data easy to collect and aggregate, including data produced by simulations, test infrastructure, training systems, and edge devices. Improve developer experience: Create self-service APIs, SDKs, tools, examples, and diagnostics that make correct data modeling and ingestion the easiest path. Drive technical direction: Evaluate emerging data and AI infrastructure technologies, make principled build-versus-buy decisions, and guide implementation across team boundaries. Raise operational quality: Establish expectations for observability, performance, reliability, security, data integrity, disaster recovery, and lifecycle management. Key outcomes: Human and agentic workflows use one coherent API for discovering data, traversing relationships, and accessing specialized payloads. Teams spend their time deciding how to model and use data rather than repeatedly deciding where and how to store it. Data produced at the edge, in simulation, during testing, and in training flows into reusable platform models with minimal integration friction. Portable and operational platform capabilities across all deployment environments. Downstream teams can adopt the platform through stable APIs and SDKs instead of custom point-to-point integrations. Required qualifications: Significant experience designing and operating distributed data solutions, storage systems, or data-intensive backend services. Strong software engineering skills and a record of delivering production systems in languages such as Go and Python. Deep understanding of data modeling, API design, schema evolution, identity, consistency, indexing, query planning, and data lifecycle concerns. Experience working across multiple storage modalities, such as relational or graph databases, object storage, analytical or columnar systems, and file storage. Experience designing reliable ingestion and access paths for high-volume or operationally important data. Strong understanding of Kubernetes, Linux, networking, security, storage, observability, and distributed-systems fundamentals. Experience deploying data infrastructure across cloud or customer-managed environments using modern Infrastructure as Code and platform engineering practices. Ability to evaluate technologies through prototypes, benchmarks, operational requirements, and total lifecycle cost rather than feature lists alone. Experience defining architecture and technical standards while remaining hands-on in implementation and debugging. Demonstrated ability to collaborate with ML researchers, autonomy engineers, test teams, platform engineers, and product stakeholders. Clear technical communication and the ability to make complex data architecture understandable to both specialists and downstream users. Bonus qualifications and relevant technologies: Experience in any of the following is beneficial but not required: Experience with specialized modern databases (eg graph, OLAP, etc...) Graph-backed retrieval, agent tooling, structured RAG, provenance-aware context construction, or explainable retrieval systems. S3-compatible APIs, cloud object storage, content-addressable storage, multipart transfer, or large-file lifecycle management. Apache Arrow, Parquet, columnar formats, time-series data, or high-performance analytical query systems. OpenAPI, AsyncAPI, WebSockets, generated SDKs, and long-lived public API contracts. Kubernetes storage and data operators, Terraform, Helm, GitOps, and repeatable platform distribution. Distributed execution technologies such as Ray and experience connecting workflow execution to data lineage and artifact management. Streaming and ingestion technologies such as Kafka, NATS, Redpanda, or comparable event-driven systems. Data and analysis in a robotics or AI domain. ML data lifecycle systems, experiment tracking, dataset management, evaluation infrastructure, feature or artifact stores, and model versioning. Observability tools, distributed tracing, and benchmarking. Data security, authorization, governance, retention, classification, and auditability across shared platforms. Why join us: The Data Platform is foundational to how Shield AI builds, evaluates, certifies, and improves autonomy. This role offers the opportunity to shape both a core internal platform and a reference architecture delivered into demanding customer environments. Your work will determine how effectively engineers and agents can find trusted context, understand provenance, aggregate data from distributed systems, and turn operational experience into better intelligent systems. You will work at the intersection of data systems, AI infrastructure, autonomy, distributed computing, and defense while helping establish the architecture that supports the next generation of mission-critical AI development.
Senior Staff Engineer, System Architect (R5843)
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: Shield AI is seeking an experienced System Architect to own the architecture of Hivemind Forge – an AI development ecosystem and the segment of Hivemind that enables developers to build, train, tune, evaluate, optimize, and deploy learning-based autonomy solutions. You will join the Systems Engineering, Integration, & Test (SEIT) team in the Hivemind Enterprise organization. This ecosystem combines developer tools, APIs, data infrastructure, simulation, AI/ML workflows, and GenAI-enabled automation to accelerate the delivery of autonomous capabilities using Vision-Language Models (VLMs), Vision-Language-Action (VLA) models, world models, foundation models, and other applied AI technologies. As the responsible architect, you will define the comprehensive architecture for this product area, maintain architectural integrity across development teams, and ensure the ecosystem can operate across enterprise cloud, high-performance computing, and secure or disconnected deployment environments. You will work at the intersection of software architecture, AI/ML, data architecture, systems engineering, developer experience, and Generative AI-enabled engineering to create an ecosystem that dramatically reduces the time required to transform mission needs and data into deployable, intelligent autonomous capabilities. What you'll do: Own and evolve the architecture of the Hivemind Forge AI development ecosystem. Define and maintain architecture products in an integrated model-based systems engineering (MBSE) environment, connecting architectural intent to engineering execution. Establish architectural patterns, interfaces, APIs, SDK concepts, and technical standards across software, AI/ML, data, simulation, and deployment capabilities. Define the data and metadata architecture underpinning the AI development lifecycle, including schemas, relationships, lineage, provenance, versioning, and lifecycle management. Ensure traceable pedigree across datasets, training configurations, model artifacts, evaluations, software versions, and deployed capabilities to support reproducibility and auditability. Architect GenAI-enabled and agentic development workflows that accelerate data curation, autonomy development, experimentation, evaluation, troubleshooting, and deployment while preserving human oversight, security, verification, and traceability. Define architectural patterns for integrating AI coding assistants, agents, foundation models, and natural-language interfaces with Hivemind development tools, APIs, SDKs, data, simulation, and engineering workflows. Define architecture for scalable AI/ML workloads across cloud, high-performance compute (HPC), and on-premises infrastructure, including orchestration, workload scheduling, containerization, storage, and data movement. Ensure the ecosystem can be deployed and operated in classified, air-gapped, disconnected, and other constrained enterprise environments while preserving security, configuration control, and reproducibility. Ensure AI-assisted and agentic development workflows preserve appropriate provenance, traceability, human oversight, verification, security, and reproducibility, particularly when contributing to deployed autonomous capabilities. Guide architecture for workflows spanning data ingestion and curation, synthetic data generation, model training and tuning, evaluation, optimization, validation, and deployment. Review and approve detailed software and data designs, resolve cross-team architectural issues, and maintain architectural integrity through implementation and integration. Partner with software, AI/ML, data, systems, product, and technical leadership teams to reduce the time from mission need to validated, deployable autonomy. Required qualifications: 10+ years of experience in software or software-intensive systems development, design, and/or architecture. Demonstrated experience architecting complex software platforms, developer ecosystems, SDKs, APIs, AI/ML platforms, or distributed systems. Experience developing AI/ML solutions using synthetic and real-world data. Experience in data modeling and data architecture, including metadata, lineage, provenance, versioning, and lifecycle management. Understanding of how data, training configurations, model artifacts, evaluations, software, and deployments must be connected to provide end-to-end traceability, reproducibility, and auditability. Experience applying Generative AI, AI assistants, or agents to software, AI/ML, or engineering development workflows. Practical understanding of technologies such as Kubernetes, Slurm or comparable workload schedulers, containerization, infrastructure as code, and object/data storage platforms such as S3-compatible systems. Strong technical leadership and communication skills, with the ability to guide detailed design and maintain alignment across multiple engineering teams. Preferred qualifications: Experience designing AI-native or agentic workflows, including tool use, orchestration, retrieval, structured outputs, evaluation, and human-in-the-loop controls. Experience with MLOps, distributed training, simulation, synthetic data generation, experiment tracking, or model registries. Direct experience developing, training, tuning, evaluating, applying, or deploying VLMs, VLAs, world models, foundation models, or related modern AI models. Experience designing, deploying, or operating software and AI/ML platforms in classified, air-gapped, disconnected, or restricted-network environments. Experience with hybrid-cloud, multi-cloud, on-premises, or edge deployment architectures. Experience architecting autonomy, robotics, aerospace, unmanned systems, or other Physical AI applications. Experience applying MBSE methods and tools, including SysML and Cameo/MagicDraw. Experience delivering defense, aerospace, safety-relevant, or other high-assurance systems requiring rigorous configuration management, verification, and traceability. Impact; You will establish the architectural foundation that enables Hivemind users to transform mission needs, data, AI models, and software into deployable autonomous capabilities—faster, repeatedly, and with confidence in how each capability was created, evaluated, and validated.
Senior Engineer, Research-to-Product Perception (R...
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: Shield AI's Hivemind Detection, Tracking, and Mapping (DTM) team develops perception capabilities that allow autonomous systems to understand objects, motion, sensors, and terrain across air, maritime, and ground domains. We are seeking a Staff Engineer to develop these capabilities from algorithms and production C++ libraries through integration, verification, and delivery in the Hivemind SDK. This is a full-stack perception product-development role. You will bring depth in at least one core area such as object detection, object tracking, computer vision, image processing, sensor modeling, or sensor fusion, and work comfortably across adjacent parts of the stack. You will help turn prototypes, research, and partner-developed technology into reusable, configurable, well-tested product capabilities. What you'll do: Evaluate emerging models and methods against representative sensor data and autonomy needs. Build prototypes and experiments that reveal strengths, limitations, and practical deployment opportunities. Combine learned and classical approaches to improve detection, tracking, geometric vision, or sensor fusion. Optimize and integrate capabilities for edge deployment, contributing Python and C++ software with support from experienced product engineers. Help deliver tested, documented capabilities and stay involved as other teams adopt them. Required qualifications: A PhD in computer vision, machine learning (ML/DL), robotics, or a related field, or an equivalent record of advanced research and hands-on engineering. Research depth in an area such as multimodal vision, visual foundation models, video understanding, open-vocabulary perception, or embodied learning. Strong Python skills and experience with PyTorch or a comparable ML framework. A thoughtful approach to experiments, evaluation data, and understanding why models fail. Experience building substantial research software, an interest in developing production-quality C++, and a collaborative approach to solving problems. Preferred qualifications: Experience bringing a research prototype into sustained use. Experience with robotics, real sensors, temporal data, or multi-sensor perception. Familiarity with vision-language models, vision-language-action models, or embodied AI. Experience with C++, edge inference, or model optimization using tools such as ONNX, TensorRT, or CUDA. You don’t need to meet every preferred qualification or arrive as an expert C++ engineer. We welcome recent PhD graduates and early-career researchers, and we value technical depth, curiosity, and enthusiasm to transfer research to business value more than publication count alone.
Principal Technical Product Manager (R5249)
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: The Special Projects team at Shield AI is an elite force within the office of the CTO. It consists of a group of very senior (L5-L8) and highly experienced software engineering experts from diverse fields (aerospace, robotics, cloud infrastructure, game development, interactive media design, ...). The charter of this group is to steer technology development towards strategic alignment with the CTO's vision, through tactical insertion into teams and technologies across the organization. Individuals within this team make direct and at times forward-sprinting contributions to all three pillars of Hivemind, Shield AI's software ecosystem for developing and deploying resilient intelligent teaming for aircrafts. Hivemind consists of four products: EdgeOS (C++ based high-performance middleware for autonomy development), Pilot (autonomy for the edge built atop EdgeOS; a models-based, modular and open architecture C++ codebase), Forge (Shield AI's AI Factory for the design, development, and testing of Hivemind Edge systems; a service-oriented architecture leveraged through an SDK, CLI, and web portal; a Go, Python, Typescript codebase), Commander (Software and hardware to support rich human-in-the-loop and human-on-the-loop interactions with the Hivemind; a C++-based back-end for interaction with Pilot; and a web-application UI for mission planning, command and control by operators implemented in a Typescript/React codebase). The Special Projects team is chartered to operate effectively within ambiguity. While this team does not own any software products, it tactically and strategically impacts the development of all foundational Hivemind products and leverages those technologies to rapidly deliver low-TRL solutions. This work happens shoulder-to-shoulder with the product teams in some cases, and in a forward-sprinting manner within the Special Projects team in other cases. The result is direct contribution to products in the former case, and development of reference implementations in the latter. The Special Projects team also functions as a pipeline for product and solution engineering teams across the organization. Individuals who enter the Special Projects team rapidly gain depth and breadth in their understanding of the Hivemind software ecosystem. This positions them well for leading technology development effort across the product and solution organization. What you'll do: Own product definition, roadmap, and metrics across the office of the CTO's agentic AI portfolio: an enterprise knowledge assistant (Brain), an agent-driven engineering platform (Springboard), and enterprise AI/data modernization and app development. Translate CTO strategy into crisp requirements, milestones, exit criteria, and KPIs — then hold the line on them. Drive adoption of internal platforms: reduce onboarding friction, instrument usage, track NPS and active users, and run developer advocacy and objection handling. Shape product direction for foundation-model based autonomy architectures and model lifecycle tooling (evaluation, fine-tuning, verification, deployment). Run continuous discovery with engineers, operators, and executive stakeholders; turn findings into prioritized backlogs. Prioritize ruthlessly across competing initiatives with small teams and aggressive timelines. Analyze the agentic tooling, enterprise AI platform, and foundation model ecosystem; recommend build/buy/partner positions to leadership. Author strategy documents, product briefs, and executive updates that drive decisions. Manage transitions of maturing products from incubation to owning organizations. Required qualifications: 8+ years of product management for deeply technical products; engineering or CS background. Technical fluency: you read code, work APIs and CLIs from a terminal, and prototype with AI coding tools yourself. Shipped developer tools, internal platforms, or AI/ML products — and drove their adoption. Working fluency in LLM-based systems: agents, evaluation, context management, fine-tuning trade-offs. Metrics-driven operating style: you define KPIs, instrument products, and report against thresholds and objectives. Exceptional written communication — requirements, strategy docs, executive briefs. Proven stakeholder management up to the executive level across engineering, product, and business functions. Fluid intelligence that allows one to operate effectively in ambiguous conditions while finding opportunities to drive technical efforts and force multiply. This role requires travel to a Shield AI location 1-3 times per quarter Preferred qualifications: Prior experience as a software engineer. Experience in defense, aerospace, or other regulated environments (CUI/ITAR, restricted or disconnected deployments). Experience with enterprise data platforms (e.g. Databricks) and ERP/business-system integration. Experience with safety-critical or assurance-driven software processes (requirements traceability, V&V, certification artifacts). Experience taking zero-to-one internal products through incubation, adoption, and handoff. Experience with robotics or autonomy products.
Technical Support Engineer (L2)
Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod to experiment, train, fine-tune, deploy, and scale AI on one platform. The platform has processed more than 20 billion inference requests. We closed a $100M Series A in June 2026. We're at an inflection point for AI infrastructure, and we're building the platform the next generation of developers will depend on. Learn more in our CEO's funding announcement: https://www.runpod.io/blog/one-million-developers. We're a small, remote-first team. We take ownership seriously, move fast, and ship work that more than a million developers rely on every day. We're looking for people who care deeply, build with urgency, and want to matter at scale. As a Technical Support Analyst (L2), you’ll play a critical role in supporting our customers by providing advanced technical assistance to resolve complex issues. This position is ideal for someone who thrives in a dynamic environment and is passionate about delivering exceptional customer service. Please note: this position requires availability on weekends as per business requirements RESPONSIBILITIES: CUSTOMER SUPPORT AND PROBLEM RESOLUTION - Provide clear, timely communication to customers, keeping them informed about the status of their issues and ensuring a high level of customer satisfaction. - Deliver support through multiple channels, including email, phone, chat, and video calls (e.g., Google Meet, Zoom). - Troubleshoot and resolve critical or complex technical issues escalated by customers, including those related to configuration, performance, functionality, compatibility, or code errors in Runpod’s products or services. - Utilize various tools and methods, such as code analysis, scripting for testing, log analysis and remote access, to identify root causes and deliver solutions or workarounds. - Communicate effectively with customers and internal teams, including engineering, sales, supply and product management teams, to ensure customer satisfaction and integrate valuable feedback. - Assist the support team in troubleshooting and resolving escalated technical tickets, collaborate with the engineering team to provide workarounds or bug fixes, and work with the infrastructure team to address GPU server-related issues. - Contribute to product development and testing efforts by relaying feedback from customers and the support team to the engineering team, helping to shape product improvements. - Create and maintain technical documentation, such as knowledge base articles, FAQs, guides, and manuals, while also developing and delivering training sessions, webinars, and demos for customers, partners, and internal teams. TECHNICAL ANALYSIS AND SOLUTIONS: - Use diagnostic tools and techniques to find the root cause of issues and implement fixes, updates, or changes as needed. - Analyze software code and logs to spot bugs or performance issues, developing solutions or workarounds where necessary. - Conduct thorough analysis of system performance, errors, and configurations to ensure our systems remain stable and reliable. - Proficiency with Datadog, Grafana, SQL databases, and ease with CRM tools are considered strong assets for this role. - Assist customers with software configuration tasks, such as installation, setup, and customization, to help them get the most out of our products. REQUIREMENTS: - At least 5 years professional experience in technical customer support. - Bachelor's degree in a relevant field (e.g., Computer Science, Computer Engineering, Software Engineering, Information Technology, or a related field) or equivalent professional experience. - Familiarity with applied AI use cases such as inference, fine-tuning, LLM-based applications, or agentic systems. - Strong problem-solving skills and the ability to analyze and resolve technical issues. - Should have at least 2 years of experience in software engineering/development or 2 years of experience as a networking admin - Knowledge of various operating systems (Linux/Ubuntu), containerization (Docker), SQL databases (MySQL, PostgreSQL), and an understanding of data center components such as server hardware and network operations, as well as familiarity with common network protocols like TCP/IP, HTTP/HTTPS, SSH, and DNS. - Ability to write and execute scripts, queries, or commands, and the ability to read and understand code, logs, errors, or traces in Python. - Excellent communication skills, both verbal and written. - Advanced knowledge of operating systems, including: - Proficiency with SSH and the use of terminal commands - Experience with Linux (server versions specifically) - Strong asset: proficiency in Docker and deployment on the docker PREFERRED: - Strong technical skills, including proficiency in Django, Flask, PyTorch, JavaScript (React, Node.js), and Go, with hands-on experience in full-stack development. - Proficiency in deploying and managing AI/ML models as services or APIs, along with a deep understanding of machine learning models, including their training, inference, and deployment processes on Runpod platforms. - Experience in AI fine-tuning or AI inference What You’ll Receive: - The competitive base pay for this position ranges from 70,000 to 93,000 usd. This salary range may be inclusive of several career levels at Runpod and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location - Meaningful equity in a fast-growing company- everyone on the team receives stock options — your impact drives our growth, and you share in the upside. - Generous medical, dental & vision plans - Flexible PTO- take the time you need to recharge - Most roles are remote work first with an inclusive, collaborative teams utilizing slack as the main form of internal communication - Join a passionate team on the cutting edge of AI infrastructure — where culture, learning, and ownership are at the heart of how we scale. - $1,200 USD Home Office & Equipment Stipend- We set you up for success from day one with gear and support to create your ideal workspace Runpod is committed to maintaining a workplace free from discrimination and upholding the principles of equality and respect for all individuals. We believe that diversity in all its forms enhances our team. As an equal opportunity employer, Runpod is committed to creating an inclusive workforce at every level. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, protected veteran status, disability status, or any other characteristic protected by law. We welcome every qualified candidate eligible to work in the United States; however, we are currently unable to sponsor employment visas
Member of Sales Staff
As a Member of Sales Staff, you will: - Own a book of prospective accounts end to end: prospecting, discovery, technical evaluation support, negotiation, and close - Run discovery calls to understand a prospect's model usage, infrastructure constraints, and business goals, and map those needs to Reka's product - Partner closely with Applied AI, Product, and Research to support technical evaluations, proofs of concept, and benchmarking exercises - Build and manage an accurate pipeline, and forecast reliably to leadership - Represent Reka at demos, meetups, and industry events as a credible voice on generative AI and model infrastructure - Work directly with leadership on strategic or complex deals given the size of the team - Help shape early sales process, positioning, and playbooks as one of the first dedicated sales hires You may be a good fit, if you have: - 3+ years of experience in sales, business development, or a customer facing technical role, selling to technical buyers or within AI, infrastructure, or developer tools - A track record of running full cycle deals and closing new business, not just generating pipeline - The ability to speak credibly about model inference, API integration, fine tuning, or compute infrastructure, or a demonstrated ability to get up to speed quickly on deep technical material - Big plus: prior experience selling AI compute or inference capacity (GPU clusters, model serving, or usage based infrastructure), you understand the buying motion around capacity commitments, utilization, and pricing - Comfort operating with a high degree of autonomy at an early stage company with limited process - Strong written and verbal communication, and the judgment to tailor a message for a developer, an ML lead, or an executive - Genuine curiosity about AI and where the market is heading REKA'S MISSION Reka's mission is to build useful multimodal artificial intelligence and use it to empower organisations and businesses. We are a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world. Our founding team, along with many of our team members, has contributed to many of the breakthroughs in AI over the past decade. WHY REKA? - An Elite Team: Collaborate with top-tier engineers, researchers, operators from renowned organizations like Google DeepMind and Facebook AI Research (FAIR) and successful startups, driving innovation in cutting-edge AI technology. - Massive Market Opportunity: Be part of a rapidly growing industry poised to transform multiple sectors globally, offering the chance to make a significant impact. - Mission-Driven Environment: Work alongside a collaborative, mission-focused team dedicated to advancing AI for meaningful applications. - Inclusive and Open Culture: Thrive in an open and inclusive work environment that values diverse perspectives and fosters creativity. - Generous Benefits: Enjoy 5 weeks of paid leave to recharge, comprehensive healthcare benefits including vision and dental, and additional perks that support your well-being.
Member of Technical Staff - Pre-Training
OUR MISSION Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all. ABOUT THE ROLE - Research and build solutions across algorithms, scaling laws, data processing, optimizers, and model architecture. - Design and run scientific experiments to advance our understanding of scaling large language models and data efficiency. - Implement state-of-the-art methods from the deep learning literature. - Lead small research projects independently while collaborating on larger initiatives - Optimize the training infrastructure for efficient scaling. - Contribute across the entire stack, from low-level optimizations to high-level model design. ABOUT YOU - Graduate degree (MS or PhD) in Computer Science, Machine Learning, or related discipline. - Solid software engineering capabilities with experience building large-scale systems. - Experience with large-scale ETL workflows and training data preparation. - Deep understanding of large-scale ML, especially as it relates to language models, distributed training, and scaling. - Proficient in Python and deep learning frameworks (PyTorch preferred). - Navigate trade-offs between research objectives and practical engineering realities. - Thrive in a fast-paced, high-agency startup environment with bias toward action. - Strong communication capabilities and comfort working collaboratively. - Passionate about advancing the frontier of intelligence. WHAT WE OFFER: We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported. - Top-tier compensation: Salary and equity structured to recognize and retain our talent globally. - Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options. - Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance. - Meals: Lunch and dinner are provided in the office daily. - Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys. - Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K. - Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable. - Team building: We have regular off-sites, happy hours, and team celebrations. Export Control Notice: This position may require access to technology or source code subject to the U.S. Export Administration Regulations. Any offer of employment for this role may be conditioned on the Company's ability to provide the candidate with access to such technology or source code in compliance with applicable U.S. export control laws, which may require the Company to seek government authorization. Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice https://cdn.sanity.io/files/irpbdun9/production/ee08c38bf22bd45a3f3a81f6a7abddb9210726b7.pdf
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