{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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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.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role  \n As a Triage Automation Engineer at Wayve , you'll play a key role in scaling our Triage and Detectives workflow through process improvement, tooling, and automation. You'll partner with Triage Specialists and Detective Engineers to turn repeated, manual analysis into reliable, productised automation, including triage bots, behavioural classifiers, and workflow tooling. That reduces manual load and speeds up how quickly we identify, understand, and resolve issues across our test and on-road fleets.\n This is a highly collaborative, detail-oriented role with a direct impact on the safety and efficiency of Wayve's development pipeline.\n Key responsibilities:\n \n Document and measure existing Triage and Detective workflows to identify opportunities for automation and process improvement\n Prioritise improvements based on cost, benefit, impact, and feasibility\n Partner with Detective Engineers to integrate their scripts and tools into scalable, productised workflows\n Work with development, ML, and AI teams to deliver the tooling improvements Triage needs\n Build automation pipelines — including triage bots and behavioural classifiers — that reduce manual load on Triage Specialists\n Validate automation changes and outputs, including the accuracy and reliability of classifications and suggested root causes\n Document newly implemented automations: what they do, how they work, how to use them, known limitations, and expected outputs\n Measure and report on triage quality and throughput to track the impact of automation\n Collaborate with senior management and cross-functional stakeholders to shape the roadmap for business-critical automation\n Willingness to travel domestically and internationally (including trips to our London office)\n \n About you   \n In order to set you up for success as a Triage Automation Engineer at Wayve, we’re looking for the following skills and experience.  \n Essential \n \n 3+ years of experience working with complex systems, ideally within robotics or autonomous vehicles\n Strong scripting and analytical skills (e.g. Python, SQL, Bash/Shell)\n Hands-on experience operating in a remote Linux environment\n Experience building or maintaining data pipelines or notebooks (e.g. Databricks, Jupyter)\n Great communication skills, able to explain complex technical problems to both technical and non-technical stakeholders\n Expertise using issue tracking and configuration management tools such as Jira, Confluence, and Bitbucket/GitLab\n Comfort with ambiguity — able to measure an existing workflow, identify where automation adds value, and scope a sensible solution\n \n Desirable \n \n Experience with web development languages (e.g. HTML, CSS, React, Java) for building internal tooling\n Practical experience with machine learning or classification models (e.g. PyTorch)\n Experience with cloud services (ideally Microsoft Azure)\n Passion for taking research ideas to production\n Track record of promoting statistical rigour and experimental best practice\n Experience working in a fast-moving tech company or startup\n \n This is a full-time role based in our office in Sunnyvale.  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. The reasonably estimated salary for this role ranges from $144,500–$183,200, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.\n  \n 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. \n 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 t","salary_min":144500,"salary_max":183200,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["autonomous-vehicles","generative-ai","robotics","data-pipeline","pytorch","evaluation"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8756182002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T17:56:55Z","expires_at":"2026-09-29T13:43:31.521698Z","created_at":"2026-08-29T13:44:35.170073Z","updated_at":"2026-08-30T13:43:31.651707Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/55f8d3f4-58f6-4ca2-9b49-1e84deeaec13"},{"id":"57b56d5b-e1f9-4118-afb8-2bd1f37d7f46","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Sr. AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector","slug":"sr-ai-engineer-fde-forward-deployed-engineer-us-federal-sector-2b0534c9","description":"PLEASE NOTE : Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply. \n The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.\n The impact you will have: \n \n Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems\n Own production rollouts of consumer and internally facing GenAI applications\n Serve as a trusted technical advisor to customers across a variety of domains\n Present at conferences such as Data + AI Summit , recognized as a thought leader internally and externally\n Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap \n \n What we look for: \n \n Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy\n Expertise in deploying production-grade GenAI applications, including evaluation and optimizations \n Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.\n Experience building production-grade machine learning deployments on AWS, Azure, or GCP\n Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience\n Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike\n Passion for collaboration, life-long learning, and driving business value through AI\n [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets\n Willing to travel once every 4-8 weeks to see customers (as needed)\n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Local Pay Range\n $182,000 — $250,208 USD \n About Databricks \n Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT\u0026T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affili","salary_min":182000,"salary_max":250208,"location":"Washington, DC","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","data-pipeline","fine-tuning","llm","generative-ai","agents"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8760168002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T14:56:34Z","expires_at":"2026-09-29T13:32:32.139503Z","created_at":"2026-08-29T13:32:27.824973Z","updated_at":"2026-08-30T13:32:32.280262Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/57b56d5b-e1f9-4118-afb8-2bd1f37d7f46"},{"id":"11b73365-9170-4b94-a834-6cf9ce41c2db","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Sr. AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector","slug":"sr-ai-engineer-fde-forward-deployed-engineer-us-federal-sector-3fa2b5eb","description":"PLEASE NOTE : Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply. \n The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.\n The impact you will have: \n \n Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems\n Own production rollouts of consumer and internally facing GenAI applications\n Serve as a trusted technical advisor to customers across a variety of domains\n Present at conferences such as Data + AI Summit , recognized as a thought leader internally and externally\n Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap \n \n What we look for: \n \n Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy\n Expertise in deploying production-grade GenAI applications, including evaluation and optimizations \n Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.\n Experience building production-grade machine learning deployments on AWS, Azure, or GCP\n Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience\n Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike\n Passion for collaboration, life-long learning, and driving business value through AI\n [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets\n Willing to travel once every 4-8 weeks to see customers (as needed)\n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Local Pay Range\n $182,000 — $250,208 USD \n About Databricks \n Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT\u0026T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affili","salary_min":182000,"salary_max":250208,"location":"Virginia","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","fine-tuning","data-pipeline","agents","llm","generative-ai"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8760167002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T14:56:31Z","expires_at":"2026-09-29T13:32:32.232912Z","created_at":"2026-08-29T13:32:27.639904Z","updated_at":"2026-08-30T13:32:32.374987Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/11b73365-9170-4b94-a834-6cf9ce41c2db"},{"id":"1a525cd5-6fd1-4af5-be1b-eaa2a3e7709e","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior ML Engineer, Core Development","slug":"senior-ml-engineer-core-development-94a264b5","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the  expertise , technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed,  built  and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a  realtime , 3D  command  and control center. As the world enters an era of strategic competition, Anduril is committed to bringing  cutting-edge  autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.   \n About the Team:   Air Dominance \u0026 Strike designs, builds, and flies autonomous air vehicles—from  collaborative combat aircraft to expendable cruise missiles and counter-UAS  interceptors. Our vehicles move from whiteboard to first flight on timelines that  traditional primes consider impossible, which means our design cycles live or die  on how fast we can close the iteration loop. The Anduril AI Engineering team  exists to collapse that loop.    \n We are engineers first. We work from engineering first principles and unlock capability through machine learning and AI. We are building to scale across CFD, FEA, thermal, and electromagnetics, with pipelines, architectures, and validation practices that carry across programs.   \n   About the Job   We are looking for a Machine Learning Engineer to apply the latest research in  physics ML to the toughest bottlenecks in our design cycle. This role owns the  entire surrogate modeling stack for Air Dominance \u0026 Strike—the architectures,  the training infrastructure, the simulation data pipelines that feed it, and the  tooling design engineers use to consume predictions.    \n   You will develop, train, and deploy surrogate models that accelerate the physics simulations underpinning our air vehicle programs. Working alongside aerodynamicists, structures engineers, and thermal engineers, your models will directly inform decisions on hardware that actually flies. Where current methods fall short, you will develop new ones, with ample room to identify novel applications of physics ML across our portfolio.    \n   Defense experience is not required. We are looking for engineers who came to machine learning through the complex physical problems they were already trying to solve.    \n   This role is based onsite in our Costa Mesa, CA office.   \n   What You'll Do   \n \n Own the Surrogate Modeling Stack:  Drive the end-to-end design, training, and deployment of production-grade surrogate models to accelerate critical simulation workflows (CFD, FEA, thermal, structural, and aeroelastic) across air vehicle design.   \n Develop State-of-the-Art Architectures:  Design and implement neural architectures tailored to engineering physics, developing new techniques for uncertainty quantification, active learning, and inverse problems (such as geometry and shape optimization).   \n Build Robust Data \u0026 Training Infrastructure:  Create the pipelines behind the training—extracting, aggregating, and sanitizing tens of thousands of high-fidelity results from solver outputs.   \n Optimize \u0026 Integrate:  Optimize inference for the design loop (maximizing GPU utilization, batched evaluation, and interactive-speed latency) and seamlessly integrate surrogate predictions into the tooling our domain engineers already use.   \n Collaborate \u0026 Mentor:  Partner with domain engineers to identify where ML delivers the highest leverage, stay current with Physics AI research, and provide technical mentorship to non ML engineers.   \n \n Qualifications   \n \n Education:  BS, MS, or PhD in aerospace, thermal, mechanical, or electrical engineering, or in machine learning/AI/data science with a demonstrated engineering foundation.   \n Experience:  3+ years of experience taking ML models from R\u0026D into production using large-scale scientific or engineering datasets.   \n Physics ML Expertise:  Working knowledge of modern surrogate architectures (e.g. GNNs, Transolver, DoMINO \u0026 GeoTransolver) comb","salary_min":220000,"salary_max":292000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["payments","tensorflow","distributed-systems","computer-vision","data-pipeline","pytorch","mlops","machine-learning"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5216691007?gh_jid=5216691007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T15:59:24Z","expires_at":"2026-09-29T13:37:22.907369Z","created_at":"2026-08-27T13:37:38.482223Z","updated_at":"2026-08-30T13:37:23.045327Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1a525cd5-6fd1-4af5-be1b-eaa2a3e7709e"},{"id":"44046e1e-69ad-4692-9110-7bb87edaadaf","company_id":"43dd17db-bec3-4ebb-a432-f71d57a9aa47","title":"Staff Software Engineer, Imaging","slug":"staff-software-engineer-imaging-4ba96095","description":"THE OPPORTUNITY\n\ninsitro is a physical AI company dedicated to unlocking causal human biology and accelerating the delivery of better medicines to patients. Our unique Virtual Human™ platform identifies novel, high-impact genetic intervention points, which our TherML™ platform translates into therapeutics—whether small molecules, biologics, or oligos. With multiple programs in metabolic disease and neuroscience advancing toward the clinic, and our first IND submission slated for the second half of this year, we are at a pivotal inflection point.\n\nAs a Staff Software Engineer on our Imaging Software team, you will define and expand our computer vision and ML infrastructure across the full imaging data lifecycle — from on-microscope acquisition to high-throughput ML pipelines. You'll build the platform features that make novel imaging modalities and ML-derived phenotypes integral to our discovery workflows, partnering daily with lab scientists, ML scientists, and our microscopy team to turn research prototypes into validated screening workflows that run reliably at laboratory automation scale. This is a chance to set the technical direction for how imaging, automation, and machine learning converge in drug discovery.\n\nBased in South San Francisco, this position reports directly to the Director of Imaging, Cellular Machine Learning and offers an in-person hybrid schedule of three days per week.\n\n\n\n\nRESPONSIBILITIES\n\nPlatform \u0026 Tooling\n\n• Platform Enablement: Partner with lab and ML scientists to design, develop, and scale the platform capabilities needed to run and interpret ML-powered high-content imaging screens\n\n• User Tooling: Build and evolve robust tools and interactive interfaces for data exploration, quality assessment, and visualization so scientists can iterate quickly on experimental data\n\n• Architectural Ownership: Own complex, end-to-end projects, making thoughtful architectural trade-offs, and delivering incrementally with long-term maintainability in mind\n\nProduction Hardening \u0026 Data Integrity\n\n• Production Hardening: Scale and harden complex image processing and ML workflows, taking them from research prototypes to systems that reliably process millions of images per day\n\n• Data Integrity: Set and uphold best-in-class practices for data integrity, lineage tracking, reproducibility, and observability across the entire imaging data lifecycle\n\n• Documentation: Write clear, exemplary technical specifications and documentation that others build on\n\nCross-Functional Partnership\n\n• Scientific Translation: Work closely with lab scientists, ML scientists, and microscopy teams to translate complex experimental needs into clear, actionable technical plans and shipped software\n\n• Mentorship: Raise the technical bar across the team by sharing knowledge and mentoring other engineers\n\n \n\n\nABOUT YOU\n\nExperience \u0026 Qualifications\n\n• Proven Tenure: 8+ years of professional experience building and operating production-grade software and high-throughput data pipelines, primarily in Python\n\n• ML Platform Depth: You have designed, built, and deployed scientific computing pipelines, visualizations, and QC processes for large-scale imaging or similarly high-dimensional datasets\n\n• Distributed Systems Stack: Hands-on experience with a Python-first ML stack, distributed compute (e.g., PyTorch/Lightning, Ray, Kubernetes), and workflow orchestration (e.g., Argo, Airflow, or redun)\n\n• End-to-End Delivery: A track record of owning complex systems from architecture through production operation\n\nCore Competencies\n\n• Cross-Functional Partnership: You thrive alongside scientists and excel at translating abstract research needs into practical, scalable software\n\n• Mission-Driven: You're motivated by enabling scientific breakthroughs through robust platform engineering\n\n• Force Multiplier: You enjoy mentoring and leveling up the engineers around you \n\n\n\n\nCOMPENSATION \u0026 BENEFITS AT INSITRO\n\nOur target starting salary for successful US-based applicants for this role is $219,000 - $233,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.\n\nThis role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.\n\n\n\nIn addition, insitro also provides our employees:\n\n - 401(k) plan with employer matching for contributions\n\n - Excellent medical, dental, and vision coverage as well as mental health and well-being support\n\n - Open, flexible vacation policy\n\n - Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)\n\n - Quarterly budget for books and","salary_min":219000,"salary_max":233000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["healthcare","payments","data-pipeline","fine-tuning","pytorch","computer-vision","distributed-systems"],"apply_url":"https://jobs.ashbyhq.com/insitro/ff6605ae-4961-4a06-b656-6d7dc665d990/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T22:43:18.642Z","expires_at":"2026-09-29T13:36:50.099247Z","created_at":"2026-08-26T13:36:56.743297Z","updated_at":"2026-08-30T13:36:50.234419Z","company_name":"Insitro","company_slug":"insitro","company_logo_url":"https://www.google.com/s2/favicons?domain=insitro.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/44046e1e-69ad-4692-9110-7bb87edaadaf"},{"id":"385357c5-623e-4db0-baf5-06182c0f554f","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Staff Machine Learning Engineer, Emergency Trajectory Models","slug":"staff-machine-learning-engineer-emergency-trajectory-models-f0038f44","description":"About us    \n 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.\n 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.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role  \n As a Staff Machine Learning Engineer in Wayve's AV Core organization, you will lead the technical direction and delivery of a learned emergency trajectory model for low-frequency, high-consequence maneuvers such as evasive steering and emergency braking. You will take the programme from problem definition through modelling, evaluation, integration, and evidence for deployment.\n Emergency maneuvers are rare, high-consequence events that place unusual demands on data, modelling, and validation. The hard problem is not simply to train another trajectory head: it is to define the operating envelope of a specialist model, what evidence shows that it improves outcomes without introducing new failure modes, and how it integrates with the general driving model and surrounding system. You will lead that work across AV Core and with partners across simulation, evaluation, safety, and product engineering.\n  \n Key responsibilities \n \n Set the technical strategy and roadmap for the emergency trajectory model, including its behavioral scope, operating envelope, system interfaces, and measurable acceptance criteria.\n Design and train trajectory-generating policies using the methods best supported by evidence, including behaviour cloning, reinforcement learning, or other sequential decision-making approaches.\n Build a data strategy for rare emergency cases, combining fleet data, targeted mining, simulation, augmentation, and reweighting while controlling coverage gaps and unintended behavior.\n Create rigorous open-loop and closed-loop evaluations for collision avoidance, evasive steering, emergency braking, recovery, robustness, latency, and regressions in nominal driving.\n Lead integration into the shared driving stack, align technical decisions across teams, and raise the bar through architecture reviews, mentoring, and clear communication of risks, trade-offs, and evidence.\n \n About you   \n In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.  \n  \n Essential  \n \n A track record of staff-level technical leadership: setting direction for ambiguous machine learning programmes, aligning multiple teams, and carrying work from research through production deployment.\n Deep expertise developing learned trajectory-generation or policy models for embodied systems, including architecture design, objective design, training, and empirical validation.\n Hands-on experience with behaviour cloning, reinforcement learning, or related methods, including objective design, distribution shift, robustness, and closed-loop failure analysis.\n Strong machine learning engineering skills in Python and PyTorch, with experience building reproducible training and evaluation systems on large, heterogeneous datasets.\n Exceptional technical judgement and communication: able to make safety-relevant trade-offs explicit, define the evidence needed for decisions, and lead without relying on formal authority.\n \n  \n Desirable  \n \n Experience applying learned models in autonomous driving or robotics, with strong understanding of motion planning, vehicle dynamics, control, or collision avoidance.\n Experience with specialist, fallback, redundant, mixture-of-experts, or model-routing architectures and the interfaces used to select between them.\n Experience mining, generating, or evaluating rare events using simulation and fleet or real-world data.\n Experience deploying learned policies under real-time latency, reliability, and compute constraints; proficiency in C++, CUDA, or systems optimisation.\n Experience with multimodal, transformer-based, diffusion-based, or other generative trajectory or policy models.\n \n This is a full-time role based in our office in Sunnyvale.  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 lear","salary_min":336400,"salary_max":370300,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","gpu","robotics","autonomous-vehicles","generative-ai","pytorch","machine-learning"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8747065002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T18:15:27Z","expires_at":"2026-09-29T13:43:29.618384Z","created_at":"2026-08-25T18:31:14.484268Z","updated_at":"2026-08-30T13:43:29.754954Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/385357c5-623e-4db0-baf5-06182c0f554f"},{"id":"9a42e317-7954-4330-9e7d-59cad3214bb9","company_id":"8115806a-6d9c-48b9-9a92-5eb180bbd1ef","title":"Applied Research Scientist, AI Research","slug":"applied-research-scientist-ai-research-428d0a90","description":"Descript's Research team builds the models behind the product's most distinctive features: Video Regenerate and lipsync, video translation, zero-shot voice and roomtone cloning, and Studio Sound. We don't build general-purpose generative models. We pick specific problems in the editing workflow and build specialized models for them. This isn't research for its own sake. Everything we build is meant to ship, and most of it has, going from prototype to a production feature used by millions of creators within months.\n This role is focused on multimodal understanding: training models to perceive edited media the way a human video editor does. Underlord, our AI editing agent, reasons about a project largely through a textual representation of it. Giving it direct perception of the media it's working on is what will let it judge its own output and reason about the creative choices in an edit, not just the structure of a project. It's also an open research problem, since there's no settled way to represent or evaluate editorial craft, whether a cut lands or whether the pacing works. We have a unique dataset to work with.\n Some recent work from the team:\n \n Audio editing by latent inpainting : regenerating a masked span of speech \n Video Regenerate : regenerating a speaker's lower face to match new or translated audio\n Jumpcut Smoothing : generating a bridge across a cut so the join plays like a continuous take\n Anchored Tree Sampling : tree-based imputation that bounds drift in long video generation\n PoDAR : disentangling power from semantics in audio latents to make them easier to model\n \n More at descript.com/research .\n What you'll do\n \n Multimodal understanding: build vision-language systems that let Descript's agentic editing features reason over the visual and audio content of a project.\n Evaluation: design the benchmarks and evals that make editorial quality measurable, and that balance quality against cost and latency.\n Data: build the datasets your work depends on, including synthetic data generation where real examples don't exist at scale.\n Training: train specialized models from scratch or fine-tune existing foundation models, whichever gets the capability we need.\n Shipping: take models from prototype to production with the agent and engineering teams.\n Direction-setting: identify the next research direction that should become a Descript feature, not just a paper. More senior candidates should expect to own this directly; more junior candidates will grow into it.\n Publishing: take your work to academic venues if you'd like. We support it, but it isn't a requirement of the role.\n \n What you bring\n Required\n \n Proven ability to design and implement deep learning algorithms, demonstrated by publications, open-source work, or models you've shipped.\n Strong programming skills and deep fluency in PyTorch.\n A track record of generating new ideas in machine learning. You produce more ideas than you can implement, and once an experiment setup is established, you can run and evaluate many of them quickly rather than being bottlenecked on infrastructure.\n Strong experimental judgment. You test ideas fast, and you're honest with yourself and the team about which ones don't pan out.\n Clear written and verbal communication, including when a direction isn't working, so the team doesn't waste time following a lead that's already dead.\n A PhD or Master's in deep learning or a related field, or equivalent experience. We care about the track record more than the credential.\n \n At least one of the following must be true:\n \n Lead or first author of an accepted publication in a top venue: CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, or similar.\n Played a key role in shipping a production feature with deep learning as a core component.\n \n More senior candidates (Senior and Staff) should also bring a track record of owning research direction rather than executing a plan handed to them, and experience mentoring or technically leading other researchers or engineers.\n Where breadth helps\n Direct experience in multimodal understanding is welcome but not required, and we don't require domain-specific expertise in computer vision or speech and audio. Our team spans both, and strong general deep learning ability transfers. We hire against the bar above, and then expect you to grow into the domain. Depth in any of these is a strong signal:\n \n Vision-language models and multimodal understanding.\n Generative modeling for video, audio, or images.\n Post-training, fine-tuning, and RL on large foundation models.\n Building evaluation systems for generative or agentic outputs where metrics resist clean definitions.\n Taking a research idea through to a shipped, production-facing feature.\n \n Compensation and benefits\n Base salary range: $197,000–$262,500, plus equity and benefits. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, and level, and may vary from the amount above.\n  \n IMPO","salary_min":197000,"salary_max":262500,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","deep-learning","fine-tuning","computer-vision","pytorch","healthcare","agents","research"],"apply_url":"https://boards.greenhouse.io/descript/jobs/7967440003?gh_jid=7967440003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T00:18:24Z","expires_at":"2026-09-29T13:35:54.489992Z","created_at":"2026-08-25T18:27:44.358668Z","updated_at":"2026-08-30T13:35:54.624927Z","company_name":"Descript","company_slug":"descript","company_logo_url":"https://www.google.com/s2/favicons?domain=descript.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9a42e317-7954-4330-9e7d-59cad3214bb9"},{"id":"241f8621-b66a-4668-ae4c-953914e72085","company_id":"b467c425-56b3-40ce-826a-e603e82a08bd","title":"Senior Software Engineer - Content Understanding","slug":"senior-software-engineer-content-understanding-ab972d21","description":"Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.  \n At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.  \n A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. \n As a Senior Software Engineer within the Creator Organization, you will develop innovative full-stack solutions that define the future of Roblox’s Content Understanding Platform. This platform processes billions of pieces of content—spanning 3D models, audio files, text, video, and entire experiences—extracting structured information about their meaning, context, and relationships. The Content Understanding Team develops cutting-edge AI models, advanced computer vision systems, and highly scalable backend platforms to power search, discovery, and moderation across Roblox. Your contributions will enable seamless asset discovery, automate moderation at scale, and drive transformative generative AI tools that reshape how millions of creators and users engage with Roblox.\n You Will: \n \n Solve full-stack challenges to improve how AI, creators, and users describe and get along with content, including images, 3D models, audio, text, and video.\n Craft and build scalable pipelines for training, evaluating, and deploying machine learning models to support content annotation and discovery.\n Develop robust backend systems to power real-time search, discovery, and powerful generative AI features.\n Blend innovation with practicality, applying the latest AI research to build impactful, production-ready solutions.\n Collaborate with engineers, product managers, and multi-functional teams to deliver bold technical projects.\n \n You Have: \n \n 7 years of strong programming skills in at least two languages (Python, C#, C++, Java) and a willingness to learn others as needed.\n Exposure to front end technologies and frameworks such as React or Angular.\n Practical experience crafting and scaling backend systems in cloud environments.\n Confirmed expertise across the stack, including backend development to deploying ML models in production environments.\n Familiarity with image or 3D object understanding, ideally within gaming or content creation industries.\n A “get stuff done” mentality with a readiness to solve challenges and take on tasks beyond your comfort zone to get results.\n A great foundation in computer vision, AI, or related fields.\n \n You Are \n \n Experience with large-scale search systems, generative AI, or semantic content understanding.\n Experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow) and end-to-end ML workflows.\n Knowledge of 3D geometry or asset workflows.\n Passion for empowering creators through innovative technology.\n For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page .\n Annual Salary Range\n $243,290 — $295,250 USD \n Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).\n Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to 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 laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.\n For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.","salary_min":243290,"salary_max":295250,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["computer-vision","generative-ai","pytorch","deep-learning","tensorflow"],"apply_url":"https://careers.roblox.com/jobs/8094470?gh_jid=8094470","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-24T22:09:19Z","expires_at":"2026-09-29T13:47:50.815075Z","created_at":"2026-08-25T18:33:06.219084Z","updated_at":"2026-08-30T13:47:50.942237Z","company_name":"Roblox","company_slug":"roblox","company_logo_url":"https://www.google.com/s2/favicons?domain=roblox.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/241f8621-b66a-4668-ae4c-953914e72085"},{"id":"d950a0af-81cc-4c4a-b562-707b97ae1ebb","company_id":"fe4d898e-86f1-400e-95db-988d7f632620","title":"Senior Director, Data","slug":"senior-director-data-460239ea","description":"Position Overview \n As our Senior Director of Data, you will serve as the strategic visionary and executive engine powering our company’s data transformation. In this high-impact leadership role, you will redefine how we leverage information by driving enterprise data strategy, pioneering AI data readiness, commanding end-to-end pipeline engineering, and unlocking competitive advantages through cutting-edge predictive analytics. You will champion, build, and inspire a world-class team across data engineering, analytics, and data science, scaling modern infrastructure, deploying production-grade ML models, and relentlessly embedding a fearless, evidence-based, data-driven culture across every level of the organization. \n Key Responsibilities \n 1. Strategy \u0026 Organizational Data Leadership \n \n \n \n Define and execute the enterprise data, AI data readiness, and analytics strategy aligned with business objectives. \n Champion a data-driven culture across departments by elevating data literacy and self-service analytics. \n Build, mentor, and lead high-performing teams of data engineers, data scientists, and analysts. \n \n \n 2. AI Readiness \u0026 Data Science Leadership \n \n \n \n Drive the AI data strategy, ensuring data is curated, labeled, and optimized for ML/AI model development and deployment. \n Oversee the end-to-end lifecycle of machine learning models, predictive analytics, and feature store infrastructure. \n Collaborate with business partners to identify high-impact AI/ML opportunities that drive strategic value. \n \n \n 3. Pipeline Engineering \u0026 Infrastructure \n \n \n \n Oversee modern data engineering, architectural design, and reliable ETL/ELT pipelines for batch and real-time processing. \n Architect scalable data warehouses, data lakes, and modern data stack operations (MLOps). \n \n \n 4. Governance, Analytics \u0026 Reporting \n \n \n \n Establish governance policies to ensure high data quality, security, and global regulatory compliance (e.g., GDPR, CCPA). \n Deliver key executive dashboards, visualizations, and A/B testing frameworks to measure operational KPIs. \n \n \n Qualifications \n \n Experience: 10+ years of progressive leadership experience across data engineering, analytics, and data science. \n Leadership: Proven track record of managing data engineering and ML teams while fostering a data-driven organizational culture. \n Technical Mastery: Strong hands-on knowledge of Python, SQL, modern ETL tools, cloud data warehouses, and major ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn). \n Architecture \u0026 Pipelines: Deep expertise in pipeline design, streaming data architectures, MLOps, and feature store management. \n Education: Master's or Ph.D. in Data Science, Computer Science, Statistics, or related quantitative field. \n Communication: Excellent capability to translate complex technical concepts into clear strategic insights for non-technical stakeholders. \n The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity. For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.\n Pay Range\n $194,400 — $432,000 USD \n  \n Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers. \n Human oversight:   Metaview does not automatically reject candidates or make final hiring decisions. Our recruiters and hiring managers review all outputs and make the final hiring decision regarding every application.  \n \n \n Your rights: If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your email here . Your decision to do so will not affect how your candidacy is evaluated. \n \n Please refer to our Candidate Privacy Notice for more information about our processing of personal data, and your rights.","salary_min":194400,"salary_max":432000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","tensorflow","mlops","data-pipeline"],"apply_url":"https://navan.com/careers/openings?gh_jid=8145890","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T16:58:39Z","expires_at":"2026-09-29T13:48:42.690923Z","created_at":"2026-08-25T18:33:21.168009Z","updated_at":"2026-08-30T13:48:42.820522Z","company_name":"Navan","company_slug":"navan","company_logo_url":"https://www.google.com/s2/favicons?domain=navan.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d950a0af-81cc-4c4a-b562-707b97ae1ebb"},{"id":"2af68795-5861-40b1-95ce-04d100978f08","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Senior Data Scientist","slug":"senior-data-scientist-e0977b92","description":"About us    \n 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.\n 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.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The Role\n As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.\n This means you might:\n \n Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success\n Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance\n Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements\n \n About you \n Essential:\n \n 3+ years experience working in a Data Science role.\n Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.\n Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics\n Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats\n Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)\n Well-versed in summarising, visualising and communicating findings in an accessible and compelling way\n Track record of influencing team direction through your findings\n A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.\n Comfortable working asynchronously across time zones with cross-functional partners\n You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.\n \n Desirable:\n \n Practical experience with machine learning (e.g. PyTorch). Passion to take research ideas to production.\n Track record of promoting statistical rigour and experimental best practices in your prior roles.\n Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.\n Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)\n Experience working in a fast-moving tech company or startup.\n \n This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably estimated salary for this role ranges from $209,700 to 266,800, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience. 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.   We operate core working hours so you can determine the schedule that works best for you and your team. \n 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. \n 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 ","salary_min":209700,"salary_max":266800,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["autonomous-vehicles","distributed-systems","pytorch","generative-ai","data-science","evaluation"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8728411002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T20:06:09Z","expires_at":"2026-09-29T13:43:27.258396Z","created_at":"2026-08-25T18:31:14.400233Z","updated_at":"2026-08-30T13:43:27.392293Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2af68795-5861-40b1-95ce-04d100978f08"},{"id":"ea9ed310-83a0-4da7-92f0-3500ba5c05a5","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior Machine Learning Engineer, Digital Twin Platform","slug":"senior-machine-learning-engineer-digital-twin-platform-081ecc8d","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale.\n We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In this role, you will develop machine learning models and deploy them into production systems, working in close collaboration with software engineers, computer vision engineers, product leads, and data scientists. If you're motivated by technically complex, high-impact problems and want to see your work shape how millions of people experience grocery shopping, this is the role for you.\n You can read more about some of the work this team is doing here:\n Introducing New Enterprise AI Solutions to Democratize AI for Grocers of All Sizes \n Instacart Acquires Arpalus to Advance Real-Time Shelf Intelligence \n About the Job \n \n Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.\n Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact.\n Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.\n Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.\n Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed — expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business.\n \n About You \n Minimum Qualifications\n \n 5+ years of experience developing and deploying machine learning models in production environments.\n Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.\n Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale.\n Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving.\n Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.\n \n Preferred Qualifications\n \n Experience working on computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling problems.\n Familiarity with real-time inference systems and the architectural considerations of serving ML models in low-latency, high-throughput environments.\n Prior experience in a fast-paced, cross-functional environment where you have independently driven projects from conception through production with limited oversight.\n Exposure to retail, supply chain, or e-commerce domains and an understanding of how inventory data flows an","salary_min":206000,"salary_max":217500,"location":"Remote (Canada)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["pytorch","tensorflow","data-pipeline","computer-vision","fine-tuning","cloud","machine-learning"],"apply_url":"https://instacart.careers/job/?gh_jid=8143147","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T19:12:31Z","expires_at":"2026-09-29T13:39:09.843919Z","created_at":"2026-08-25T18:28:59.914166Z","updated_at":"2026-08-30T13:39:09.978396Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ea9ed310-83a0-4da7-92f0-3500ba5c05a5"},{"id":"f4154f18-d97b-44e2-af31-0a213ace915e","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior Machine Learning Engineer, Digital Twin Platform","slug":"senior-machine-learning-engineer-digital-twin-platform-85efdb23","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale.\n We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In this role, you will develop machine learning models and deploy them into production systems, working in close collaboration with software engineers, computer vision engineers, product leads, and data scientists. If you're motivated by technically complex, high-impact problems and want to see your work shape how millions of people experience grocery shopping, this is the role for you.\n You can read more about some of the work this team is doing here:\n Introducing New Enterprise AI Solutions to Democratize AI for Grocers of All Sizes \n Instacart Acquires Arpalus to Advance Real-Time Shelf Intelligence \n About the Job \n \n Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.\n Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact.\n Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.\n Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.\n Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed — expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business.\n \n About You \n Minimum Qualifications\n \n 5+ years of experience developing and deploying machine learning models in production environments.\n Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.\n Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale.\n Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving.\n Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.\n \n Preferred Qualifications\n \n Experience working on computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling problems.\n Familiarity with real-time inference systems and the architectural considerations of serving ML models in low-latency, high-throughput environments.\n Prior experience in a fast-paced, cross-functional environment where you have independently driven projects from conception through production with limited oversight.\n Exposure to retail, supply chain, or e-commerce domains and an understanding of how inventory data flows an","salary_min":201000,"salary_max":212000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["cloud","pytorch","computer-vision","fine-tuning","tensorflow","data-pipeline","machine-learning"],"apply_url":"https://instacart.careers/job/?gh_jid=8143145","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T19:12:30Z","expires_at":"2026-09-29T13:39:09.752316Z","created_at":"2026-08-25T18:28:59.910126Z","updated_at":"2026-08-30T13:39:09.886675Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f4154f18-d97b-44e2-af31-0a213ace915e"},{"id":"30922887-a8eb-4d71-b922-a837aef04ace","company_id":"4c0fefc3-173a-4227-a823-4d67d3e70ff0","title":"Senior Research Engineer","slug":"senior-research-engineer-9f57f845","description":"Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.\n Our base salary range is $174,240 - $261,360, and in addition we have generous bonus plans to provide a competitive compensation package. \n Who You Are: \n OlmoEarth is growing — more partners, more use cases, and a platform that is evolving quickly. We are looking for a Senior Research Engineer who can collaborate with our partners to tailor the OlmoEarth models to a wide range of specific applications across multiple domains. \n Who We Are:  \n OlmoEarth is an open, end-to-end platform built around a family of foundation models for Earth observation. The platform enables users to create custom fine-tuned models to detect and classify novel geospatial features, handling the full loop: imagery acquisition, annotation, distributed model training and inference, and visualization.\n Our partners span some of the most respected institutions working on wildfire risk, crop mapping, mangrove conservation, and forest protection. OlmoEarth sits within the AI for the Planet group at the Allen Institute for AI, a small, mission-driven team working on conservation, food security, disaster resilience, and climate solutions.\n Learn more: https://allenai.org/olmoearth \n What We Believe \n \n The mission is the point. OlmoEarth exists to put powerful Earth observation tools into the hands of people working on conservation, food security, and climate. Every partner engagement this role supports is connected to that goal. If it matters to you that your day-to-day work adds up to something larger, you are in the right place.\n Good operations are invisible and indispensable. When coordination, documentation, and follow-through are working well, the whole team moves faster and partners have a better experience. This role is the engine behind that.\n Our partners are the signal. We learn what to build and how to improve by staying close to the people using the platform. The feedback, patterns, and friction you surface in this role directly shapes what the team works on next.\n In-person matters. A lot of the best work on this team happens in quick, unplanned conversations between engineering, research, and partnerships. We are mostly in the office because that is where this kind of collaboration happens naturally.\n Say what you think. We make better decisions when people share what they are actually seeing — whether that is a process that is not working, a partner need we are missing, or an idea for doing something differently. Everyone here is still learning, and we like it that way.\n \n Your Next Challenge: \n You will work with partners to deploy OlmoEarth for their use cases. This will require you to move fluidly across the entire OlmoEarth team, working with partners, engineers and researchers. You will make meaningful contributions to all the components of OlmoEarth’s infrastructure (from the finetuning code to model pretraining to our rslearn backend).\n Use case enablement \n \n Collaborate closely with partners to deploy OlmoEarth models in challenging contexts. This will prioritize contexts and partners for which we don’t have immediate solutions or there’s an opportunity to standardize a high quality approach for common use cases.. \n Explore novel use cases for the OlmoEarth models (e.g. post-hoc addition of new modalities, effectively leveraging embeddings in different contexts) which can unlock new use cases and partners.\n \n Partner Communications \u0026 Coordination \n \n As part of model development, maintain communications with key partners to ensure their success using the OlmoEarth platform.\n Communicate  internally  so that partner needs are clearly understood by the OlmoEarth machine learning research, engineering and partnership teams. \n \n Product Improvement and Research \n \n Work closely with the engineering and partnerships  team to feed lessons you learn when deploying models into our infrastructure. This includes improvements to rslearn, OlmoEarth Studio. \n Collaborate with the research team to identify and fix issues with the OlmoEarth models preventing their deployment in specific important applications. \n Continually update our model adaptation approaches to improve model performance for all our partners. This includes updating our fine-tuning approaches, developing recipes for new applications and improving the UI so that modelling trade-offs can be better understood by users. \n Support agent evaluations and development.\n \n What You’ll Need: \n Required\n \n 2+ years of experience deploying machine learning solutions. This covers the full stack of machine learning, including understanding the business case and requirements, training models, and deploying them at scale.\n Technical experience using machine learning tools. This includes fluency in PyTorch, experience debugging traini","salary_min":174240,"salary_max":261360,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","search","robotics","pre-training","fine-tuning","generative-ai","research"],"apply_url":"https://job-boards.greenhouse.io/thealleninstitute/jobs/8140098","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T18:47:01Z","expires_at":"2026-09-29T13:47:18.072158Z","created_at":"2026-08-25T18:32:53.66843Z","updated_at":"2026-08-30T13:47:18.202634Z","company_name":"Allen Institute for AI","company_slug":"allen-institute-for-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=allenai.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/30922887-a8eb-4d71-b922-a837aef04ace"},{"id":"d29bfaad-c593-4c53-93b1-dff4b4c64a86","company_id":"adc4981a-d4ff-4939-952f-362f51e1291d","title":"Sr. Machine Learning Engineer","slug":"sr-machine-learning-engineer-3ba58cf5","description":"Our Mission: \n 6sense's mission is to multiply what matters: growth, retention, and efficiency.  We envision a future where companies, teams and people reach their full potential.\n Our People: \n People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging.  Every 6sensor plays a part in defining the future of our industry-leading technology.  6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers.  We want 6sense to be the best chapter of your career. \n \n About 6sense\n 6sense is Intelligence for Agentic GTM. We turn every signal — yours and ours — into intelligence that every team, tool, and AI agent can act on and trust. Every day, the 6sense Signalverse™ captures one trillion signals to power AI that pinpoints who’s ready to buy, how to engage them, and when to act. 6sense was named a Leader in The Forrester Wave™: Revenue Marketing Platforms for B2B, Q1 2026.\n The Opportunity\n We’re hiring a Senior Machine Learning Engineer to join our AI team, reporting directly to the Head of AI.\n Signals tell you what happened. Our job is to explain why — and that is the problem you will work on. You will build the intelligence that turns a trillion daily signals into cited, explainable answers about why an account matters, why now, and who is deciding. Your models power products customers use every day, including RevvyAI, our conversational GTM intelligence product, and reach their stack through our APIs and MCP server.\n This is a build-and-ship role, not a research role. You will own problems end to end, work directly with Product and Go-to-Market, and see your work reach customers. You’ll join a team distributed across the US and India, at a company where AI is the product rather than a feature.\n What You’ll Do\n \n Own machine learning problems end to end — from data exploration and modeling through deployment, monitoring, and iteration in production.\n Build NLP, LLM, and agentic systems at enterprise scale, including retrieval-based architectures and multi-agent workflows.\n Develop ranking, recommendation, prediction, and optimization models that are explainable rather than black-box.\n Partner with Product and Go-to-Market to turn ambiguous business problems into shipped capabilities.\n Improve the performance, scalability, and reliability of production ML systems, and help shape AI platform architecture.\n Explain your work clearly to technical and non-technical audiences, and engage with customers when needed.\n Mentor engineers and raise the bar for engineering excellence.\n \n What We’re Looking For\n Required\n \n 8+ years of industry experience building and deploying machine learning systems in production, with clear end-to-end ownership.\n Strong foundation in machine learning and applied statistics, with hands-on depth in NLP, transformers, embeddings, and retrieval-based systems.\n Practical experience with modern GenAI tooling such as LangGraph, LangChain, or Amazon Bedrock.\n Strong Python skills and experience building distributed ML pipelines on cloud infrastructure (AWS, Databricks, or equivalent).\n Solid grasp of feature engineering, model evaluation, and MLOps practices.\n A product mindset — you want to build AI products customers use, and you measure yourself on customer impact.\n Excellent communication: you can explain complex technical work clearly, tell the story of what you’ve built and why, and hold your own with product and business partners.\n Comfort with ambiguity and the judgment to drive execution independently.\n \n Nice to Have\n \n Experience with RAG architectures, vector databases, and prompt engineering.\n Hands-on work with PyTorch or TensorFlow.\n Background in B2B SaaS, enterprise AI products, or forward-deployed engineering — especially where you worked directly with complex customer data and delivered quickly.\n \n  \n Base Salary Range: $200,349.50 - $260,912.60. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote \n Notice of Collection and Use of Personal Information for California Residents: California Recruitment Privacy Notice and Policy \n Our Benefits:   \n Full-time employees can ta","salary_min":200349,"salary_max":260912,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["tensorflow","nlp","fine-tuning","rag","generative-ai","pytorch","payments","llm"],"apply_url":"https://boards.greenhouse.io/6sense/jobs/8064973?gh_jid=8064973","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T15:47:30Z","expires_at":"2026-09-29T13:41:04.935693Z","created_at":"2026-08-25T18:30:07.718512Z","updated_at":"2026-08-30T13:41:05.080754Z","company_name":"6sense","company_slug":"6sense","company_logo_url":"https://www.google.com/s2/favicons?domain=6sense.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d29bfaad-c593-4c53-93b1-dff4b4c64a86"},{"id":"640a0e13-d4ff-4740-9c87-66a1c123f740","company_id":"19955a21-2cd6-41fd-a4a8-19b7a942ac16","title":"Lead Applied Value Engineer – CPG \u0026 Retail","slug":"senior-applied-value-engineer-cpg-retail-cf50e017","description":"Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet.\n Role Description As a Lead Applied Value Engineer, you will push the envelope in solving business-critical problems for strategic customers within our Consumer Packaged Goods (CPG) \u0026 Retail Vertical. You will partner with our most important clients to understand their unique objectives—from global supply chain resilience and trade promotion optimization to inventory shrink reduction and large-scale margin expansion programs. By combining the world’s leading Process Intelligence (PI) platform with technologies from top AI and ML partners (Microsoft, OpenAI, Databricks), you will build innovative solutions that drive measurable impact.\n Using our PI platform, we feed operational context to AI, bridging ERP, WMS, POS, and e-commerce platforms so it understands our customers’ complex commercial realities. This enables CPG brands and retailers to industrialize AI and unlock real ROI at scale. You will prototype these solutions, demonstrate their value to CPG and retail executives, and ensure successful implementation, adoption, and value realization to expand our footprint across the global retail and consumer ecosystem.\n Key Responsibilities \n \n \n AI Discovery \u0026 Solutioning: Understand customers' AI strategies and sector-specific challenges (e.g., demand forecasting, out-of-stock prevention, shelf placement, trade spend analytics). Find the best problem-solution fit and translate business requirements into innovative, needle-moving solutions.\n \n Pre- and Post-Sales Execution: Drive the full customer lifecycle. Lead technical discovery and capability demonstrations during pre-sales, and remain deeply involved post-sale to guide implementation and ensure agreed value and adoption thresholds are met.\n \n Hackathons \u0026 Prototyping: Leverage cutting-edge AI technologies to rapidly build creative prototypes during customer hackathons. Solve critical pain points specific to inventory routing, fulfillment, and promotional alignment with a proactive, \"can-do\" approach.\n \n Agentic Process Transformation: Shift customers from traditional, rule-based automation to autonomous AI agents empowered by Process Intelligence (e.g., autonomous inventory replenishment, intelligent deduction management), ensuring real ROI on AI deployments.\n \n Proof Projects: Architect and execute business-critical Proof-of-Value projects. Deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, integrating seamlessly with enterprise retail data, identity protocols, and consumer data privacy frameworks.\n \n Domain \u0026 Industry Leadership: Serve as the primary technical subject matter expert for the CPG and retail sectors. Scale deep domain expertise across the organization to deliver high-value solutions for global brands, mega-retailers, and distribution partners.\n \n Smart Warehouse \u0026 Fulfillment Operations: Champion modern distribution initiatives. Specialize in warehouse management system (WMS) optimization, RFID inventory tracking, micro-fulfillment centers, dynamic order routing, and fulfillment center workflows for high-velocity retail operations.\n \n Omnichannel \u0026 DTC Transformation: Act as a technical advisor on the transition to seamless omnichannel and Direct-to-Consumer (DTC) execution. Optimize order-to-cash cycles, customer returns processing, dynamic pricing models, and loyalty program integrations.\n \n Sustainable Supply Chain \u0026 Eco-Fulfillment: Drive technical strategy for sustainable retail operations. Focus on tracking Scope 3 emissions, optimizing cold-chain efficiency, reducing perishable food waste, and streamlining sustainable packaging workflows across the distribution network.\n \n Requirements \n \n \n Experience: 8+ years leading end-to-end technical pre-sales and post-sales engagements within the CPG, retail, or e-commerce space. Proven ability to define AI roadmaps, build compelling ROI/TCO business cases, and guide technical implementations to value realization.\n \n Domain Expertise: Deep understanding of retail and CPG business processes. In-depth experience in domains such as Inventory Management, Supply Chain, Trade Promotion, Category Management, or Loss Prevention, with the ability to translate strategic requirements into impactful solutions.\n \n Technical Proficiency:","salary_min":196000,"salary_max":230000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","agents","generative-ai","pytorch","cloud"],"apply_url":"https://job-boards.greenhouse.io/celonis/jobs/7831220003?gh_jid=7831220003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T13:39:49Z","expires_at":"2026-09-29T13:38:49.942437Z","created_at":"2026-08-25T18:28:53.543891Z","updated_at":"2026-08-30T13:38:50.079076Z","company_name":"Celonis","company_slug":"celonis","company_logo_url":"https://www.google.com/s2/favicons?domain=www.celonis.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/640a0e13-d4ff-4740-9c87-66a1c123f740"},{"id":"0dfb8aab-f030-4de8-ae57-e7eae9cdd25c","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Senior Machine Learning Engineer, Vision Models","slug":"senior-machine-learning-engineer-vision-models-b67985dc","description":"About us    \n 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.\n 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.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role \n As a Senior Machine Learning Engineer on Wayve's Measurement team in AI Evaluation, based in our Sunnyvale office, you will build the computer vision and scene understanding models Wayve uses to measure the performance of the Wayve Driver offline. You will adapt technology from our on-vehicle models and Wayve Foundation Models into offline models that understand coverage, mine rare events, and assess driving behaviour, and you will drive their accuracy and generalisation across vehicles, markets, and conditions. Measuring your own models rigorously is part of the work. You will define ground truth and correctness criteria across a complex driving taxonomy, and turn them into automated benchmarks and evidence that our validation pipelines and safety cases can stand on.\n The Measurement team builds and qualifies the scene understanding models Wayve uses to measure driving performance offline, after on-road runs and in simulation. Offline is where the interesting headroom is: more compute per frame, larger foundation models, and access to both past and future temporal context that the vehicle never has. The outputs are mission-critical, directly informing model development decisions and customer deliverables. You will work in a focused, high-impact senior team with strong ownership, access to fleet-scale camera, lidar, and simulation data, and close partners across on-vehicle modelling, evaluation, data curation, and simulation.\n Key responsibilities \n \n Develop the models - build, train, and fine-tune the scene understanding models at the centre of Wayve's offline measurement, adapting on-vehicle architectures and Wayve Foundation Models for offline use.\n Drive accuracy and generalisation - improve model performance across vehicle platforms, geographies, and driving conditions; diagnose failure modes and close the loop on blind spots.\n Exploit the offline environment - use the advantages the vehicle does not have: higher compute budgets, larger model capacity, bidirectional temporal context, and multi-task or joint representation learning.\n Measure what you build - benchmark your models, set quality bars, and use metrics and error analysis to steer the next iteration; treat measurement as the feedback that drives the modelling.\n Make the evidence credible - ensure benchmarked results are statistically defensible and fit to feed validation pipelines at scale and our broader safety cases, across the product portfolio.\n Align priorities and mentor - work day-to-day with on-vehicle modelling, evaluation, data curation, and simulation teams across sites; contribute to strong engineering and modelling practice; mentor others on the team; understand how the team's priorities connect to the wider division..\n \n About you  \n In order to set you up for success as a Senior Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.  \n Essential  \n \n 4+ years in ML engineering, including training and shipping deep learning models in production, comfortable taking ambiguous modelling problems from scoping through to a working solution.\n Hands-on experience training modern computer vision models, including transformer-based and multimodal or VLM architectures for detection, segmentation, classification, or scene understanding, on camera and/or lidar sensor data.\n Experience adapting or fine-tuning large pretrained or foundation models, and training shared representations across multiple tasks or objectives (multi-stage or joint training), including real trade-offs across data and losses.\n Proficient in Python and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices and comfort with large-scale training.\n Strong ownership: research-literate and pragmatic, able to drive a significant modelling workstream with autonomy, collaborate across teams, and mentor less experienced engineers.\n Able to measure your own models: comfortable defining and","salary_min":311850,"salary_max":370000,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","computer-vision","fine-tuning","generative-ai","autonomous-vehicles","pytorch","robotics","distributed-systems"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8728757002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T20:07:14Z","expires_at":"2026-09-29T13:43:27.827274Z","created_at":"2026-08-25T18:31:14.421095Z","updated_at":"2026-08-30T13:43:27.960326Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0dfb8aab-f030-4de8-ae57-e7eae9cdd25c"},{"id":"6aabed50-4dbf-497c-bf63-c12df13dba87","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Lead Machine Learning Engineer","slug":"lead-machine-learning-engineer-d35ab649","description":"May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. \n We are seeking Machine Learning Leaders in the Autonomous Vehicle domain. As part of our team, you will play a critical role in enhancing May’s Machine Learning capabilities both on and off the vehicle, in a commercial large-scale environment with high standards of quality.\n Essential Responsibilities \n \n Design, train and evaluate state of the art models for May’s autonomous driving, simulation and ML Platform stack.\n Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems.  \n Lead small teams of cross functional Engineers beyond the state of the art.\n Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale.\n \n Skills and Abilities \n Success in this role typically requires the following competencies:\n \n Direct experience architecting \u0026 training VLA, MMLM, or Generative World Models for commercial-scale applications\n Experience composing, processing and characterizing large (\u003e100TB) multi-modal datasets\n Experience analyzing and addressing long-tail failure cases in large models\n Experience leading teams of 2-3 Engineers and communicating technical details to interdisciplinary leadership.\n \n Qualifications and Experience \n Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:\n Required \n \n Extensive practical experience in one of the following domains:\n \n Vision Language Action Models\n Generative World Models\n Foundation Models in Robotics\n Data Centric AI\n \n A minimum of 4 years of industry experience working on commercial robotics systems.\n A minimum of 1 year mentoring ML Engineers in a commercial or lab environment.\n Master’s degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation.\n Practical experience handling the “Long Tail” problem in Machine Learning.\n Strong programming skills in Python/PyTorch in a Linux environment.\n Functional understanding of LiDAR, Camera and Radar processing techniques.\n \n Desirable \n \n PhD and/or published research in the described specialty domains.\n Familiar with common post-training techniques.\n Experience deploying models to resource constrained and edge hardware\n Functional understanding of C/C++/CUDA memory and threading models.\n \n Physical Requirements \n \n Standard office working conditions which includes but is not limited to:\n \n Prolonged sitting\n Prolonged standing\n Prolonged computer use\n \n Travel required? -  Low: 5%-10%\n \n \n \n \n \n \n \n \n Benefits and Perks \n \n Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. \n Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.\n Rich retirement benefits, including an immediately vested employer safe harbor match.\n Generous paid parental leave as well as a phased return to work. \n Flexible vacation policy in addition to paid company holidays.\n Total Wellness Program providing numerous resources for overall wellbeing   \n \n Don’t meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we’re committed to building a diverse, inclusive, and authentic workforce, so if you’re excited about this role but your previous experience doesn’t align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May.\n Want to learn more about our culture \u0026 benefits? Check out our  website ! \n May Mobility is an equal opportunity employer.  All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual ","salary_min":220000,"salary_max":270000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["healthcare","autonomous-vehicles","generative-ai","robotics","pytorch","gpu","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8730957002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T19:14:18Z","expires_at":"2026-09-29T13:47:53.465471Z","created_at":"2026-08-25T18:33:06.96684Z","updated_at":"2026-08-30T13:47:53.592694Z","company_name":"May Mobility","company_slug":"may-mobility","company_logo_url":"https://www.google.com/s2/favicons?domain=maymobility.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6aabed50-4dbf-497c-bf63-c12df13dba87"},{"id":"88c598ce-9fe7-4103-ba06-6a02f5b5f2f2","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Senior ML/AI Modeler, Risk Automation Machine Learning","slug":"senior-mlai-modeler-risk-automation-machine-learning-d62ab6c1","description":"Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.\n The Role \n The Risk Automation ML team automates Risk and Compliance investigations and decision making at Block through the application of agentic and generative AI technology. We work globally with partners in Product, Engineering and Operations to ensure that we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.\n We are leveraging agentic and generative AI as an integral part of our toolkit to fulfill our mission. Block's machine learning systems monitor billions of payment transactions across traditional payment and blockchain networks and surface suspicious activity (fraudulent, suspicious, illegal activity and brand violations) for trained Operations analyst review and decisioning. We are leveraging generative AI to accelerate historically manually intensive analyst workflows; by adding features in the investigative UX to accelerate agent productivity and enable them to make faster, more informed and accurate decisions (aka Copilots). We also automate workflows end to end completely eliminating the need for manual reviews (aka Autopilots).\n This is a new and significant opportunity to rethink and optimize Risk Operations at Block at scale. This is an IC role, but the senior level has significant leadership responsibilities that include owning, and driving strategic roadmaps \u0026 priorities to completion by collaborating with relevant cross functional stakeholders.\n (Work from anywhere: This role can be performed from any location in the United States and Canada)\n You Will \n \n Experiment and deploy AI copilot and autopilot systems at scale to improve analyst productivity and/or eliminate manual decision loops altogether.\n Own the end to end system including API calls to disparate data sources, advanced prompt tuning, orchestration, metrics and evaluation, productionization and monitoring.\n Leverage diverse data sets that include payment transactions, connected users and asset graphs, unstructured text data and user profile information to build transformer based ML models to improve downstream detection tasks.\n Work cross functionally with product, platform, engineering and operational stakeholders to deploy production grade systems and monitor and tune ongoing performance.\n Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP \u0026 AWS) to get the job done.\n Leverage agentic tools (Claude Code/Codex/Openclaw) to supercharge your research, development, devOps and documentation work as part of your day to day.\n \n You Have \n \n 8+ years of Machine Learning modeling experience. Full stack ML experience is strongly preferred.\n A Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field.\n 3+ yrs experience with AI engineering, Large language models, and a background in traditional NLP techniques is a strong plus for this role.\n End to end experience of building and deploying ML/AI to production systems (batch and real time) that are performant at scale.\n Experience of independently owning, influencing and driving programs with multiple cross functional stakeholders that have significant business impact.\n Have a curious, growth-oriented mindset and the ability to think in first principles to identify creative solutions that demonstrate value.\n \n  \n We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and \"fair chance\" ordinances.\n We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page .\n While there is no specific deadli","salary_min":194500,"salary_max":291700,"location":"San Francisco, CA","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["cloud","payments","llm","agents","generative-ai","nlp","pytorch","code-generation"],"apply_url":"http://block.xyz/careers/jobs/5394441008?gh_jid=5394441008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T18:24:19Z","expires_at":"2026-09-29T13:39:46.526987Z","created_at":"2026-08-25T18:29:18.489401Z","updated_at":"2026-08-30T13:39:46.664819Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/88c598ce-9fe7-4103-ba06-6a02f5b5f2f2"},{"id":"b1638ac7-d1b2-4de0-b991-6d17c0656bb6","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Staff Gen AI Research Scientist ","slug":"staffgenai-research-scientist-f60a2c4a","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM   \n The Air Dominance \u0026 Strike team at Anduril develops aerial and multi-domain robotic systems. The team is responsible for taking products like Fury (unmanned fighter jet) and Barracuda (air-breathing cruise missile) from concept to product. The team also develops Lattice for Mission Autonomy, Anduril’s premier software platform that enables masses of Fury, Barracuda, and other first and third party robots to collaborate across various missions. We work in close coordination with specialist teams like Perception, Motion Planning, Hardware, and Test Engineering to solve some of the hardest problems facing our customers. We are looking for AI research scientists, Applied scientists and roboticists excited about creating a powerful autonomy software stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications.   \n ABOUT THE JOB   \n We are seeking an  AI Research Scientist  to serve as a founding ML expert on our team. In this role, you will design, fine-tune, and deploy the next generation of generative AI, LLMs, and agentic systems that power our air-dominance platforms and collaborative autonomous behaviors.    \n This is a highly applied research role  (split roughly 60% applied research/experimentation and 40% hands-on coding)  focused on making state-of-the-art LLM models smaller, faster, and smarter. You will work on both offboard systems (for complex mission planning, modeling, and simulation) and onboard systems—optimizing models to run directly on power- and compute-constrained edge hardware. As an early member of this initiative, you will have significant autonomy to set the technical direction, design our data collection strategy across test sites and simulations, and directly influence how multi-agent autonomy is deployed in critical missions.   \n WHAT YOU’LL DO   \n \n Develop, pre-train, and fine-tune in-house LLMs and multimodal foundation models. Apply SOTA post-training alignment techniques (SFT, RLHF, DPO) to maximize capability while minimizing cost and footprint. \n Architect and optimize models to run directly on tactical edge compute and power-constrained hardware onboard physical assets. Optimize model latency, memory usage, and execution speed through quantization, distillation, and pruning. \n Design and implement robust agentic architectures, multi-agent coordination frameworks, and planning loops for complex, multi-domain military missions. \n Collaborate closely with computer vision, perception, and motion planning teams to build systems capable of reasoning over diverse modalities, including camera feeds, radar, telemetry, and text-based operational orders. \n Define and execute data collection strategies across physical assets, test sites, and virtual simulations. Work with AI Infrastructure engineers to build scalable evaluation frameworks that measure model performance, reliability, and safety in high-stakes environments. \n Build early-stage prototypes alongside customers, quickly iterate on feedback, and scale those prototypes into production-grade features deployed across our family of systems.   \n \n REQUIRED QUALIFICATIONS   \n \n Strong production-level coding skills in Python and deep learning frameworks (like PyTorch or JAX).  \n Hands-on experience training, fine-tuning, and evaluating LLMs, Generative AI, or multimodal models. \n A strong background in a classical technical discipline (Computer Vision, NLP, Robotics, or Speech) with 2+ years of dedicated experience focusing on generative models and modern transformer architectures. \n Experience using modern model training, alignment, and orchestration tools (e.g., Axolotl, Hugging Face, DeepSpeed, Megatron-LM, LangChain, or LlamaIndex). \n Ability to operate comfortably in a fast-paced environment, moving from ambiguous mission requirements to concrete code and functional prototypes. \n Degree (B.S., M.S., or Ph.D.) in Computer Science, Machine Learning, Robotics, Physics, Mathematics, or a related technical field. \n Eligible to obtain and maintain an active U.S. Top Secret security clearance.   \n \n PREFERRED QUALIFICATIONS   \n \n Proven track record of compiling and running deep learning models on edge accelerato","salary_min":220000,"salary_max":292000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","cloud","payments","robotics","diffusion-models","generative-ai","pytorch","nlp"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5216230007?gh_jid=5216230007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T16:20:23Z","expires_at":"2026-09-29T13:37:30.58848Z","created_at":"2026-08-25T18:28:19.681085Z","updated_at":"2026-08-30T13:37:30.721438Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b1638ac7-d1b2-4de0-b991-6d17c0656bb6"},{"id":"7ed7422c-421c-4fee-b478-a18ac174105a","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Principal Machine Learning Engineer, Geometric Vision","slug":"principal-machine-learning-engineer-geometric-vision-81629411","description":"About us    \n 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.\n 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.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role  \n As a Principal Engineer on the Model Foundations team you will  build the geometric vision and 3D foundation models that underpin our autonomous driving systems.You will work at the intersection of large-scale deep learning, geometric computer vision, and real-world robotics, developing models that learn 3D structure and dynamics from fleet-scale sensor data.\n You will be a hands-on technical leader. You will set direction for geometric vision, prototype and train new model architectures, build the data and supervision needed to scale them, and take successful ideas through to deployment on real vehicles.\n Key responsibilities \n \n Design and train 3D foundation models and world models using large-scale driving data.\n Develop model architectures for 3D perception, geometric reasoning, reconstruction, and world modeling across space and time.\n Build scalable data generation and auto-labeling pipelines that produce high-quality geometric supervision from large volumes of sensor data.\n Develop and scale offline SLAM and 3D reconstruction systems and pipelines, using large-scale sensor data to recover accurate trajectories, scene geometry, calibration signals, and geometric supervision for model training and evaluation.\n Develop and apply techniques in multi-view geometry, neural rendering, NeRFs, Gaussian Splatting, implicit 3D representations, and feedforward 3D modeling.\n Explore geometry-aware tokenization and representation learning, including efficient ways to encode and fuse information across cameras, viewpoints, time, and sensing modalities.\n Develop foundation vision models that make effective use of camera, radar, LiDAR, and other sensor data for learning rich representations of the physical world.\n Explore video and generative modeling approaches for learning scene structure, dynamics, and future evolution from driving data.\n Train and evaluate models at scale on distributed compute, rapidly iterating on architectures, objectives, data, and training recipes.\n Develop automated evaluation and ground-truth systems for measuring geometric consistency, reconstruction quality, 3D understanding, and downstream driving performance.\n Optimize and deploy models into production autonomous-driving systems, working across model architecture, inference, and onboard constraints.\n Set technical direction for geometric vision at Wayve and work closely with researchers and engineers across foundation models, perception, simulation, data, sensing, and deployment.\n \n About you   \n In order to set you up for success as a Principal Machine Learning Engineer, Geometric Vision at Wayve, we’re looking for the following skills and experience.  \n Essential  \n \n Deep expertise in 3D computer vision, geometric vision, or 3D machine learning, with experience in areas such as multi-view geometry, neural rendering, reconstruction, implicit representations, or world modeling.\n Strong experience designing, training, and evaluating modern deep-learning models at scale, using PyTorch or a comparable framework.\n Strong mathematical and technical foundations in geometry, linear algebra, probability, optimization, and 3D transformations, combined with excellent software engineering skills in Python and C++\n A track record of taking difficult research problems from idea to working system, including building large-scale data, training, evaluation, or deployment pipelines.\n Principal-level technical leadership: the ability to identify high-leverage problems, set research and engineering direction, make strong architectural decisions, and raise the technical bar across teams.\n \n Desirable  \n \n 3D and geometric vision: multi-view geometry, dense 3D reconstruction, neural fields, NeRFs, Gaussian Splatting, or feedforward 3D models.\n Foundation and world models: large-scale vision pre-training, self-supervised learning, video models, generative models, or learned scene dynamics.\n Geometric data engines: offline SLAM, stru","salary_min":407330,"salary_max":460020,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["computer-vision","robotics","distributed-systems","autonomous-vehicles","pre-training","pytorch","generative-ai","deep-learning"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8724862002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-18T19:30:55Z","expires_at":"2026-09-29T13:43:25.9237Z","created_at":"2026-08-25T18:31:14.335359Z","updated_at":"2026-08-30T13:43:26.052776Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7ed7422c-421c-4fee-b478-a18ac174105a"}],"page":1,"per_page":20,"total":887,"total_is_exact":true,"total_pages":45}