{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google's parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you're ready to do the greatest work of your life, come join us. \n About the Program:  \n Join Wing's 12-week paid summer internship! This is a hybrid, in-person program based in Palo Alto, CA, with start dates in May or June. Eligible candidates must be a current student enrolled in a degree program and intend to return to the program after the completion of the summer internship. \n About the Opportunity: \n Wing is looking for a Machine Learning Engineer Intern to join our Perception team based in Palo Alto, CA. You will be at the forefront of advancing our autonomous drone delivery system, leveraging deep learning to ensure our aircraft navigate the world with precision and safety.  At Wing, you aren’t just building models in a vacuum; you have access to tens of thousands of hours of flight data from a diverse sensor suite\n In this role, you will: \n \n Help us track towards our goal of building unified and/or generalized Perception models that helps Wing aircraft systems gracefully handle a wide variety of edge cases they experience when operating in the real world\n Analyze real-world data, coming up with new ideas on how to improve our existing Perception pipelines with state-of-the-art foundational and end-to-end geometric models\n Gain experience with leveraging large amounts of diverse, real-world data from a fleet of thousands of robots to build ML models that solve real problems.\n Make a measurable impact on Wing's ability to scale our operations more rapidly, at the forefront of the rapidly growing drone delivery industry.\n Be a part of a dynamic and collaborative team.\n \n What You’ll Need:  \n \n Currently pursuing a Master's, or PhD degree in Aerospace Engineering, Mechanical Engineering, Computer Science, Computer Vision, Robotics, Electrical Engineering, or related field, graduating between December 2027 and August 2028\n Strong examples of previous engineering experience from past internships and/or academic or extracurricular projects.\n Strong grasp of basic physics and engineering fundamentals in Computer vision\n Strong grasp of modern computer vision technologies such as self-supervised Vision Transformer foundation model, Vision Language Models, VLAs, and hands-on experience in at-least one of those domains\n Experience with C++ and/or Python.\n The US base salary range for this internship position is the salary range below + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process.\n Salary Range\n $128,000 — $135,000 USD \n Wing is an equal opportunity employer and it is Wing's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person's merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.\n If you have a need that requires accommodation during the interview process due to a disability or special need, please let us know by completing our  Candidate Accommodations Request Form .","salary_min":128000,"salary_max":135000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["robotics","computer-vision","cloud","deep-learning","generative-ai","machine-learning"],"apply_url":"https://wing.com/careers/8872479002?gh_jid=8872479002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T22:00:01Z","expires_at":"2026-11-13T17:02:54.727732Z","created_at":"2026-10-14T15:24:57.757978Z","updated_at":"2026-10-14T17:02:54.730712Z","company_name":"Wing","company_slug":"wing","company_logo_url":"https://www.google.com/s2/favicons?domain=wing.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8ad2920a-4171-4759-864b-2007360008f4"},{"id":"2bdabd0b-9451-4388-b502-2ba7d839c43f","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Machine Learning Engineer, Drive","slug":"senior-machine-learning-engineer-drive-202e134e","description":"About the Team\n DoorDash Drive powers deliveries placed through merchants' own channels—including their websites, mobile apps, and phone orders—using DoorDash's logistics network. The Drive Machine Learning team builds the prediction and intelligence systems that power this business, including delivery and pickup time estimation, merchant prep-time prediction, order release optimization, logistics decision-making, and AI-powered delivery quality signals. Drive presents a unique machine learning challenge. Every merchant has different operational workflows, preparation patterns, and customer expectations, requiring models that generalize across millions of deliveries while adapting to highly diverse merchant behavior. Our team has significant opportunities to improve prediction accuracy, optimize logistics decisions, and build AI-native experiences that directly improve merchant, consumer, and dasher outcomes.\n About the Role\n As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration. Your work will span several high-impact problem areas:\n \n Build next-generation machine learning models for delivery ETA, pickup ETA, merchant prep-time estimation, and order release prediction that improve reliability for merchants and consumers.\n Develop deep learning models that leverage large-scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.\n Apply reinforcement learning and optimization techniques to improve logistics decision-making, assignment strategies, and marketplace efficiency.\n Build AI-native product experiences using large language models (LLMs) and vision-language models (VLMs). For example, transform pickup photos, item verification flows, receipts, and drop-off images into structured quality signals that help verify orders, prevent delivery defects, and improve issue resolution.\n Design and run rigorous online experiments, production monitoring, and model iteration to continuously improve performance.\n Partner closely with software engineers, product managers, data scientists, and platform teams to bring new machine learning capabilities into production at scale.\n You'll have the opportunity to work across traditional machine learning, deep learning, reinforcement learning, optimization, and multimodal AI while solving some of the most challenging logistics problems at DoorDash.\n \n You're excited about this opportunity because... \n \n You enjoy solving large-scale machine learning problems that directly impact millions of deliveries.\n You have a strong sense of ownership and enjoy taking models from research through production.\n You're comfortable working in ambiguous environments where experimentation and iteration drive product decisions.\n You care about both model quality and production reliability.\n You're excited to work across a diverse set of ML techniques—from neural networks and optimization to multimodal AI.\n You collaborate well across engineering, product, and data science teams.\n \n We’re excited about you because… \n \n 5+ years of industry experience building and shipping production machine learning systems with measurable business impact (Bachelor's, Master's, or PhD).\n Strong experience developing production machine learning models using modern deep learning frameworks such as PyTorch and distributed data processing technologies such as Spark and Airflow.\n Experience building, deploying, monitoring, and maintaining production ML systems end-to-end.\n Strong software engineering skills in Python and experience with modern ML infrastructure and tooling.\n Deep expertise in at least one of the following areas:\n \n Deep Learning\n Reinforcement Learning\n Optimization / Operations Research\n Large Language Models (LLMs) or Vision-Language Models (VLMs)\n \n Experience applying machine learning to estimation, ranking, prediction, optimization, or decision-making problems at production scale.\n Hands-on experience with LLMs or VLMs is a strong plus.\n Experience in logistics, marketplaces, or delivery platforms is helpful but not required.\n Proficiency using AI-assisted development tools (e.g. Claude Code, Codex, Cursor) throughout the software development lifecycle.\n You are located or are planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA.\n Compensation \n The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions.  Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about yo","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","deep-learning","reinforcement-learning","cloud","llm","generative-ai","healthcare","pytorch"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8221807","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:42:26Z","expires_at":"2026-11-13T17:03:28.706911Z","created_at":"2026-10-14T15:25:31.350903Z","updated_at":"2026-10-14T17:03:28.710264Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2bdabd0b-9451-4388-b502-2ba7d839c43f"},{"id":"634e56a9-b38d-474b-847e-3dc417b38339","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Machine Learning Engineer, Personalization","slug":"staff-machine-learning-engineer-personalization-d2d9e9a7","description":"About the Team \n Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop modern growth and personalization models that power DoorDash's growing retail and grocery business.\n About the Role \n We’re looking for a passionate Applied Machine Learning expert to join our team. As a Staff Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the growth and personalization experiences at the heart of our fast-growing grocery and retail delivery business.  You will use our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across grocery, convenience, and many other retail categories. You will demonstrate a strong command of production level machine learning,  experience with solving end-user problems, and collaborate well with multi-disciplinary teams.\n You will report into the engineering manager on our Personalization team. We expect this role to be hybrid with some time in-office and some time remote (#LI-Hybrid).\n You’re excited about this opportunity because you will… \n \n Develop production machine learning solutions to build a world class personalized shopping experience for a diverse and expanding retail space\n Partner with engineering and product leaders to help shape the product roadmap applying ML\n Mentor junior team members, and lead cross functional pods to create collective impact\n \n You can find out more on our ML blog here \n We’re excited about you because you have… \n \n 8+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. \n Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software\n M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field\n Expertise in applied ML for  Causal Inference and Recommendation Systems  -  both classical and deep learning based. Additional familiarity with explore/exploit/MAB algorithms \u0026 LLMs is a plus.  \n Machine learning background in Python; experience with PyTorch or TensorFlow preferred.\n Ability to communicate technical details to nontechnical stakeholders\n You keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down\n Desire for impact with a growth-minded and collaborative mindset\n \n \n Data Retention, Privacy \u0026 Bias Audit: Data collected during this process is retained in accordance with our Candidate Privacy Policy and applicable state laws. In compliance with New York City Local Law 144, the independent bias audit summary for Gem is publicly available for review at our Careers Page . \n Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only\n We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.\n The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey \n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","cloud","deep-learning","fine-tuning","healthcare","pytorch","tensorflow","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8225006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:31:26Z","expires_at":"2026-11-13T17:03:28.796671Z","created_at":"2026-10-14T15:25:31.438732Z","updated_at":"2026-10-14T17:03:28.799759Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/634e56a9-b38d-474b-847e-3dc417b38339"},{"id":"501a4fae-853d-480b-9dbb-39daa44f8047","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Machine Learning Engineer, Fulfillment Planning","slug":"staff-machine-learning-engineer-fulfillment-planning-53570b60","description":"About the Team \n The Fulfillment Planning team builds the intelligence that powers DoorDash’s logistics network. We optimize how deliveries are planned and executed across the full delivery lifecycle, improving customer experience, merchant outcomes, Dasher efficiency, and DoorDash profitability.  Our mission is to improve fulfillment quality while reducing fulfillment cost. We do this by applying machine learning, optimization, and systems engineering to the core decisions behind assignment, routing, batching, timing, and fulfillment estimation.\n The team works on some of DoorDash’s most important logistics systems, including:\n \n The core assignment engine that matches deliveries with Dashers in real time.\n Real-time ETA and fulfillment estimation systems for consumers, Dashers, and merchants across diverse geographies and all business lines.\n Assignment and planning algorithms for specialized delivery types, including grocery, retail, parcel, and catering.\n ML models and optimization algorithms that shape demand, improve service quality, and reduce cost.\n Tier-0 logistics services that require high reliability, low latency, and strong operational discipline.\n \n The team also builds reusable ML systems and modeling patterns that scale across DoorDash’s logistics ecosystem. This role will help define the technical direction and best practices for logistics ML at DoorDash.\n About the Role \n We’re looking for a Staff Machine Learning Engineer to lead the design, development, and deployment of large-scale production ML systems that drive real-time decisioning across DoorDash’s fulfillment ecosystem.\n You will start by owning ML systems for assignment and fulfillment estimation, partnering closely with Product, Data Science, Engineering, and Platform teams to improve delivery quality, cost, and efficiency. Over time, you may also contribute to adjacent areas such as batching, fulfillment execution, demand shaping, and logistics optimization across DoorDash’s business lines.\n This is a high-impact individual contributor role for someone who enjoys building 0→1 ML systems, operating at Staff-level scope, and influencing technical direction across multiple teams. You will define architectures, set modeling and deployment standards, mentor other engineers, and help shape how DoorDash applies machine learning to logistics at scale.\n You’re excited about this opportunity because you will… \n \n Own and build foundational ML systems that directly impact delivery quality, cost, and overall logistics efficiency across DoorDash.\n Work on challenging, real-world machine learning problems , including real-time assignment, routing, and fulfillment estimation.\n Lead 0→1 ML initiatives , defining how machine learning and optimization are applied across fulfillment products.\n Influence architecture, strategy, and execution for a Tier-0 service critical to DoorDash’s logistics platform.\n Collaborate closely with Product, Data Science, and Platform Engineering in a highly cross-functional environment.\n Establish best practices for model development, deployment, monitoring, retraining, and governance.\n Define and lead DoorDash’s cutting-edge AI vision for logistics: an LLM-inspired foundation model for intelligence across logistics\n Mentor other engineers and raise the technical bar for logistics ML across the organization.\n \n We’re excited about you because… \n \n You have 8+ years of industry experience building and deploying production-scale machine learning systems.\n You have strong machine learning fundamentals and know how to apply them to large-scale production systems.\n You are fluent in Python\n You have hands-on experience with modern ML frameworks, especially deep learning frameworks.\n You have designed, launched, and operated mission-critical ML models or systems in production, including monitoring, retraining, reliability, and governance.\n You can lead complex technical projects end to end and influence stakeholders across multiple teams or organizations.\n You communicate clearly with both technical and non-technical audiences.\n You are comfortable operating in ambiguous problem spaces and turning 0→1 ideas into production systems.\n You have built or shipped large-scale ML models for recommendation, ads, marketplace, logistics, or other domains.\n You have experience with knowledge distillation from large teacher models into efficient production models.\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares ","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","healthcare","cloud","generative-ai","llm","deep-learning","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8224336","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:30:37Z","expires_at":"2026-11-13T17:03:28.79242Z","created_at":"2026-10-14T15:25:31.434336Z","updated_at":"2026-10-14T17:03:28.795093Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/501a4fae-853d-480b-9dbb-39daa44f8047"},{"id":"362dd4a4-f865-4d4a-9a7a-bc7e1b3dff50","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Staff Machine Learning and Bioinformatics Scientist (Multi-Cancer Early Detection)","slug":"staff-machine-learning-and-bioinformatics-scientist-multi-cancer-early-detection-df2fad4b","description":"Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients.\n PRIMARY RESPONSIBILITIES: \n \n Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data\n Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group\n Prototype, test and productionize ML models using scalable infrastructure\n Own key technical deliverables within larger projects and help shape the team’s research roadmap\n Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies\n Keep raising the bar through code and design reviews across projects\n Translate complex results into clear stories for technical and non-technical audiences\n Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence\n \n QUALIFICATIONS: \n \n PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD\n Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data\n Proven track record of innovation and technical leadership in complex method development projects\n Expertise in deep learning and multimodal foundation models\n Proficient in Python and its scientific computing ecosystem\n Scientific rigor throughout the R\u0026D process, with eagerness to teach and learn new computational methods and biology\n Excellent communication skills and a collaborative approach across teams\n \n Preferred Experience: \n \n Familiarity with DNA methylation and other epigenomic data\n Experience with cell-free DNA and liquid biopsy samples\n Background in cancer genomics and diagnostics\n Hands-on work with multimodal foundation models applied to biological data\n The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years \u0026 depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.\n Remote USA\n $163,200 — $204,000 USD \n OUR OPPORTUNITY \n Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.\n The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.\n WHAT WE OFFER \n Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!\n For more information, visit www.natera.com .\n Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.\n All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability or any other legally protected status. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws.\n If you are based in California, we encourage you to read this important information for California residents.  \n Link: https://www.natera.com/notice-of-data-collection-california-residents/ \n Please be","salary_min":163200,"salary_max":204000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["generative-ai","deep-learning","healthcare","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6220885004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T22:10:48Z","expires_at":"2026-11-13T16:58:38.001158Z","created_at":"2026-10-14T15:22:15.63645Z","updated_at":"2026-10-14T16:58:38.003762Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/362dd4a4-f865-4d4a-9a7a-bc7e1b3dff50"},{"id":"51543c6e-0d4b-4d56-b403-d772dc9cc157","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Staff Machine Learning and Bioinformatics Scientist (Multi-Cancer Early Detection)","slug":"staff-machine-learning-and-bioinformatics-scientist-multi-cancer-early-detection-bbaf4d4a","description":"Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients.\n PRIMARY RESPONSIBILITIES: \n \n Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data\n Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group\n Prototype, test and productionize ML models using scalable infrastructure\n Own key technical deliverables within larger projects and help shape the team’s research roadmap\n Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies\n Keep raising the bar through code and design reviews across projects\n Translate complex results into clear stories for technical and non-technical audiences\n Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence\n \n QUALIFICATIONS: \n \n PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD\n Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data\n Proven track record of innovation and technical leadership in complex method development projects\n Expertise in deep learning and multimodal foundation models\n Proficient in Python and its scientific computing ecosystem\n Scientific rigor throughout the R\u0026D process, with eagerness to teach and learn new computational methods and biology\n Excellent communication skills and a collaborative approach across teams\n \n Preferred Experience: \n \n Familiarity with DNA methylation and other epigenomic data\n Experience with cell-free DNA and liquid biopsy samples\n Background in cancer genomics and diagnostics\n Hands-on work with multimodal foundation models applied to biological data\n \n Compensation \u0026 Total Rewards  \n This range reflects a good-faith estimate of the base pay we reasonably expect to offer at the time of  hire. Final compensation will vary based on experience, qualifications, and internal equity considerations. \n This position is also eligible for additional compensation and benefits through Natera’s robust Total Rewards program, including: \n \n \n Annual performance incentive bonus \n \n Long-term equity awards \n \n Comprehensive health benefits (medical, dental, vision) \n \n 401(k) with company match \n \n Generous paid time off and company holidays \n \n Additional wellness and work-life benefits \n \n \n Compensation Range \n $169,800 — $212,300 USD \n OUR OPPORTUNITY \n Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.\n The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.\n WHAT WE OFFER \n Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!\n For more information, visit www.natera.com .\n Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.\n All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability","salary_min":169800,"salary_max":212300,"location":"San Carlos, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","deep-learning","healthcare","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6221940004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T22:10:46Z","expires_at":"2026-11-13T16:58:37.997051Z","created_at":"2026-10-14T15:22:15.640367Z","updated_at":"2026-10-14T16:58:37.999729Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/51543c6e-0d4b-4d56-b403-d772dc9cc157"},{"id":"943a5e5f-5b9a-4c60-ae1f-a9319c87ec0e","company_id":"4bc4e268-7a05-4a65-a162-1688af546f7e","title":"Senior Machine Learning Programmer","slug":"senior-machine-learning-programmer-dd417989","description":"WHAT MAKES US EPIC?\n At the core of Epic’s success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it’s building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we’re always innovating.\n Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development.\n PROGRAMMING - SPECIAL PROJECTS\n What We Do \n The Special Projects team at Epic is responsible for executing high-impact projects that push the envelope to define the future of real-time graphics and gaming technology (The Matrix Awakens, Lumen in the Land of Nanite). In collaboration with the Unreal Engine team, we strive to put our technology and knowledge into the hands of users, empowering developers and content creators with the most powerful suite of real-time tools in the world.\n What You'll Do \n You will work with our team of applied research programmers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create state-of-the-art tools to support game developers in our ecosystem with a focus on bots (trained gameplay agents, intelligent NPCs, companions, world modeling), as well as automation of a number key areas (including moderation, security, and QA testing). You will be responsible for the design, implementation and deployment of production-ready machine learning models that can be integrated in our ecosystem.\n In this role, you will \n \n Create and deliver production-ready, scalable and high-quality machine learning models and associated algorithms that can make actions in game environments\n Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap\n Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones\n \n What we're looking for \n \n PhD in Computer Science, Mathematics or related field, or 3+ years of relevant industry experience\n Experience creating / applying machine learning algorithms for action modeling of bots behavior, vision-based or language-instructed, and deploying them as production-level systems in-game\n Expert, hands-on knowledge of:\n \n Deep learning, incl. but not limited to applications in the gaming industry\n Foundational models and vision and/or language, especially vision-language-action models, reinforcement learning agents, incl. local deployment and model post-training of open weights models\n Reinforcement learning, incl. experience with agentic systems, reward design, policy optimisation, evaluation, and building scalable training environments for agents\n Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch)\n \n Experience with working collaboratively with other developers, following a flexible/agile/lean approach\n \n This role is open to multiple locations across North America \u0026 Europe (including NYC). \n Pay Transparency Information \n The expected annual base pay range(s) for this position are detailed below. Each base pay range is relevant only for individuals who are residents of or will be expected to work within the specified locale. Compensation varies based on a variety of factors, which include (but aren’t limited to) things such as skills and competencies, qualifications, knowledge, and experience. In addition to base pay, most employees are eligible to participate in Epic’s generous benefit plans and discretionary incentive programs (subject to the terms of those plans or programs). \n New York City Base Pay Range\n $232,666 — $341,243 USD \n ABOUT US\n Epic Games​ ​is a leading interactive entertainment company. For over 30 years we've been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world-class talent.\n Like what you hear? Come be a part of something Epic! \n Epic Games deeply values diverse teams and an inclusive work culture, and we are proud to be an Equal Opportunity employer. Learn more about our Equal Employment Opportunity (EEO) Policy here .\n Note to Recruitment Agencies: Epic does not accept any unsolicited resumes or approaches from any unauthorized third party (including recruitment or placement agencies) (i.e., a third party with whom we do not have a negotiated and validly executed agreement). We will ","salary_min":232666,"salary_max":341243,"location":"BLANK,BLANK,Multiple Locations","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","pytorch","deep-learning","reinforcement-learning","nlp","computer-vision","machine-learning"],"apply_url":"https://epicgames.com/careers/jobs/6221662004?gh_jid=6221662004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T19:46:26Z","expires_at":"2026-11-13T17:02:44.874623Z","created_at":"2026-10-14T15:24:47.963173Z","updated_at":"2026-10-14T17:02:44.878058Z","company_name":"Epic Games","company_slug":"epic-games","company_logo_url":"https://www.google.com/s2/favicons?domain=epicgames.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/943a5e5f-5b9a-4c60-ae1f-a9319c87ec0e"},{"id":"58d65f8c-9bfe-4e0f-8026-f55da835720b","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Staff Machine Learning Engineer","slug":"staff-machine-learning-engineer-9c39e036","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n Staff Machine Learning Engineer, CX Intelligence \n  \n CEE Intelligence (CEEI) is the ML and intelligence layer for Coinbase's customer engagement ecosystem, building customer intelligence, evaluation systems, routing and classification models, safety guardrails, and decisioning capabilities that power Help Center, chat, voice, agent tooling, and other customer support runtimes. As a Staff Machine Learning Engineer, you'll lead the design and delivery of production ML systems across the org, shaping technical strategy, building scalable intelligence capabilities, and partnering with product and engineering stakeholders to improve resolution quality, automation coverage, safety, and customer experience. What you'll do: \n \n Own the design and delivery of production ML systems, applying LLMs, deep learning, graph neural networks, and classical ML techniques to solve complex customer experience problems.\n Partner with leadership and cross-functional stakeholders to define strategic roadmaps and translate vision into quarterly execution plans with measurable outcomes.\n Lead high-impact ML projects end-to-end, from architecture through production, managing priorities, risks, and dependencies.\n Build scalable, secure, and reliable ML systems, evaluation pipelines, and data workflows using high-quality, well-tested Python code.\n Mentor engineers and establish team-wide standards for design, testing, observability, and operational excellence.\n Drive design reviews covering security, responsible AI, model quality, and architectural integrity, improving reliability, scalability, and latency across the stack.\n \n Required Skills and Experience: \n \n 8+ years of experience in machine learning and software engineering, with proven success building, scaling, and maintaining production ML systems, data platforms, or analytical services.\n Hands-on expertise with one or more of LLMs, deep learning, graph neural networks, gradient-boosted trees, or regression, combined with strong knowledge of NLP, information retrieval, data mining, or advanced statistics.\n Strong Python skills with demonstrated ability to write maintainable, highly tested production code for ML services.\n Experience mentoring engineers and raising technical standards across a team or organization, including leading design reviews and influencing technical and non-technical stakeholders.\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n \n Job #: P77568\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $218,025 — $256,500 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":218025,"salary_max":256500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["generative-ai","llm","nlp","deep-learning","search","machine-learning"],"apply_url":"https://www.coinbase.com/careers/positions/8267151?gh_jid=8267151","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T19:31:10Z","expires_at":"2026-11-13T16:58:01.54146Z","created_at":"2026-10-14T15:21:41.463785Z","updated_at":"2026-10-14T16:58:01.544331Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/58d65f8c-9bfe-4e0f-8026-f55da835720b"},{"id":"208f6a9b-9968-46f0-aa68-f972d885cce0","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-fc07da4b","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198500,"location":"Boston, MA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["autonomous-vehicles","robotics","mlops","deep-learning","data-pipeline","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=8016984003#/8016984003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T17:27:51Z","expires_at":"2026-11-13T16:56:23.376677Z","created_at":"2026-10-14T15:20:30.457065Z","updated_at":"2026-10-14T16:56:23.379931Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/208f6a9b-9968-46f0-aa68-f972d885cce0"},{"id":"70e145b8-5b41-4b48-a424-a088b204b2a6","company_id":"b467c425-56b3-40ce-826a-e603e82a08bd","title":"[2027] Senior Machine Learning Engineer - PhD Early Career","slug":"2027-senior-machine-learning-engineer-phd-early-career-b6d69cf2","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 At Roblox, we believe advanced research belongs in production, driving core algorithmic advances at a global scale. In this role, you’ll own high-impact projects end-to-end, from initial ideation to production deployment and academic publication, while solving complex, high-dimensional challenges at world-scale concurrency. \n Your expertise, across research areas including Computer Vision and Graphics, multimodality, NLP, or recommendation systems, will directly shape the experience for millions of daily active users. Come build the AI-driven infrastructure powering the future of immersive entertainment.\n You Will \n \n Prototype and implement advanced AI and machine learning solutions that drive core platform features and innovation at scale.\n Develop and deploy cutting-edge models (e.g., deep learning, generative AI, multimodal architectures) to solve complex, high-impact technical challenges.\n Collaborate with applied researchers, engineers, and product teams to translate advanced research concepts into production-ready systems.\n Translate complex research into scalable, robust infrastructure that directly impacts hundreds of millions of daily active users.\n Work backward from user and product needs to architecture, and deliver ML solutions that improve platform engagement, safety, and content ecosystem growth.\n \n You Have \n \n Possess or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.\n Deep expertise and curiosity in a relevant technical domain, such as deep learning, computer vision, NLP, reinforcement learning, or distributed systems.\n Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.\n A strong research track record, evidenced by multiple publications and presentations in rigorous peer-reviewed venues.\n \n You may redact age, date of birth, and dates of attendance/graduation from your resume.\n As you apply, you can find more information about our process by signing up for Speak_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.\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 $196,750 — $243,290 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":196750,"salary_max":243290,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["computer-vision","deep-learning","distributed-systems","generative-ai","nlp","reinforcement-learning","machine-learning"],"apply_url":"https://careers.roblox.com/jobs/8242623?gh_jid=8242623","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T16:05:13Z","expires_at":"2026-11-13T17:02:53.108743Z","created_at":"2026-10-14T15:24:56.108637Z","updated_at":"2026-10-14T17:02:53.113421Z","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/70e145b8-5b41-4b48-a424-a088b204b2a6"},{"id":"d6ccab06-8408-4826-b3a1-259ba586f060","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Software Engineer, Machine Learning Platform - MDX","slug":"software-engineer-machine-learning-platform-mdx-445b9a46","description":"About the Team \n Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented engineers to help us create and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.\n About the Role \n At DoorDash, our Data Scientists and ML Engineers have the opportunity to dive into a wealth of delivery data to improve company-wide ML workflows such as Search \u0026 Recommendations, Dasher Assignment, ETA Prediction, and Dasher Capacity Planning. You will join a small team to build systems that empower efficient machine learning at scale. This is a hybrid opportunity in San Francisco, Sunnyvale or Seattle.\n You’re excited about this opportunity because you will…\n \n Build a world-class ML platform where models are developed, trained, and deployed seamlessly\n Work closely with Data Scientists and Product Engineers to evolve the ML platform as per their use cases \n You will help build high performance and flexible pipelines that can rapidly evolve to handle new technologies, techniques and modeling approaches\n You will work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day\n You will help design and drive directions for the centralized machine learning platform that powers all of DoorDash's business.\n Improve the reliability, scalability, and observability of our training and inference infrastructure.\n \n We’re excited about you because… \n \n B.S., M.S., or PhD. in Computer Science or equivalent\n Exceptionally strong knowledge of CS fundamental concepts and OOP languages\n 2+ years of industry experience in software engineering\n Prior experience building machine learning systems in production such as enabling data analytics at scale\n Prior experience in machine learning - you've developed and deployed your own models - even if these are simple proof of concepts\n Systems Engineering - you've built meaningful pieces of infrastructure in a cloud computing environment. Bonus if those were data processing systems or distributed systems\n \n Nice To Haves \n \n Experience with challenges in real-time computing\n Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure\n Familiar with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow\n Familiar with Spark, MLLib, Databricks,MLFlow, Apache Airflow, Dagster and similar related technologies.\n Familiar with large language models like GPT, LLAMA, BERT, or Transformer-based architectures\n Familiar with a cloud based environment such as AWS\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).\n \n The national base pay range for this position within the United States, including Illinois and Colorado.\n $130,600 — $192,000 USD \n About DoorDash\n At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order fo","salary_min":130600,"salary_max":192000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["healthcare","pytorch","cloud","llm","deep-learning","distributed-systems","fine-tuning","tensorflow"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8264534","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T14:17:34Z","expires_at":"2026-11-13T17:03:28.767496Z","created_at":"2026-10-14T15:25:31.409011Z","updated_at":"2026-10-14T17:03:28.770438Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d6ccab06-8408-4826-b3a1-259ba586f060"},{"id":"5d06e771-bce8-47ec-ab25-c7a09a6ec39e","company_id":"545e1785-0a1e-478e-b21c-cb7ffa7e0b88","title":"Senior Machine Learning Engineer, Vehicle Perception","slug":"senior-machine-learning-engineer-vehicle-perception-6d396019","description":"Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.\n\nOur work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud \u0026 AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.\n\n\nTEAM\nThe Vehicle Perception team at Woven by Toyota tackles the core challenges of machine learning for 3D perception, sensor fusion, and computer vision in autonomous vehicles. Our work involves a variety of challenges, such as analyzing petabytes of multimodal driving data, solving optimization problems in computer vision, minimizing latency on hardware accelerators, deploying scalable and efficient machine learning (ML) training and evaluation pipelines, and designing novel neural network architectures to advance state-of-the-art ML for onboard perception. We are looking for doers and creative problem solvers to join us in improving mobility for everyone with human-centered automated driving solutions for personal and commercial applications.\nWHO ARE WE LOOKING FOR?\nThe team is looking for a skilled Machine Learning Engineer to help advance a cutting-edge machine learning system for perception foundation models leveraging large-scale multimodal sensor data. You will have the chance to design and implement innovative machine learning models for our next-generation autonomous vehicle platform, influencing millions of Toyota production vehicles. We are looking for individuals who are passionate about self-driving car technology and its potential impact on humanity. Furthermore, we highly value candidates who exhibit a \"giver\" mindset, consistently seeking opportunities to assist their colleagues while maintaining a strong focus on delivering solutions to production.\n","salary_min":140000,"salary_max":230000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","deep-learning","autonomous-vehicles","computer-vision","machine-learning"],"apply_url":"https://jobs.lever.co/woven-by-toyota/68d72c7e-e867-45e8-b81b-3315889bea75/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T16:35:57.897Z","expires_at":"2026-11-13T17:00:18.00542Z","created_at":"2026-10-14T15:23:51.750868Z","updated_at":"2026-10-14T17:00:18.008985Z","company_name":"Woven by Toyota","company_slug":"woven-toyota","company_logo_url":"https://www.google.com/s2/favicons?domain=woven.toyota\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5d06e771-bce8-47ec-ab25-c7a09a6ec39e"},{"id":"bed4ba83-1003-483b-ae16-2e373644bf3e","company_id":"b6e5a3d1-9bde-4a82-8d78-9f38ed99ee81","title":"Staff Research Scientist - Foundation \u0026 World Models ","slug":"staff-research-scientist-foundation-world-models-95a79182","description":"As a Staff Research Scientist within Datadog AI Research (DAIR), you will drive research in foundation models and world models as a hands-on individual contributor. You will advance large-scale pre-training and multimodal learning across the diverse signals generated by distributed systems, including metrics, traces, logs, topology, and events. You will set the technical direction for ambitious research programs, raise the technical bar for the researchers and research engineers around you, and collaborate with Datadog's product and engineering teams to translate research advances into products. \n  \n What You'll Do: \n \n Drive research in foundation models, world models, and multimodal learning, shaping the technical direction of ambitious research programs grounded in observability\n Own research problems end to end, from framing the question through experimentation, model development, and evaluation\n Train large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities\n Advance approaches to pre-training, representation learning, world modeling, scaling, and evaluation for models that learn the dynamics of complex distributed systems\n Raise the technical bar across the team by reviewing research directions, mentoring researchers and research engineers, and setting standards for experimental rigor\n Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities\n Contribute to research publications, present at top-tier conferences such as NeurIPS, ICLR, and ICML, and help open-source key model artifacts and benchmarks\n \n  \n Who You Are: \n \n You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as foundation models, world models, multimodal learning, or generative modeling\n You have driven technically ambitious research at meaningful scale as an individual contributor, whether in an industry research lab, startup, academic environment, or another research setting\n You have extensive hands-on experience designing, training, and evaluating large-scale deep learning models (such as large language models), with experience in multimodal or non-text data considered a strong plus\n You have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements\n You set technical direction through influence rather than authority, and you have mentored other researchers or engineers and elevated the quality of work around you\n You want to stay deeply hands-on in research for the long term, and you can communicate complex research findings effectively across technical and non-technical audiences\n \n  \n Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. \n  \n About Datadog:  \n Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.\n  \n Equal Opportunity at Datadog: \n Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.\n  \n Your Privacy: \n Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice.\n  \n Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness rei","salary_min":320000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","healthcare","deep-learning","generative-ai","pre-training","search","llm","research"],"apply_url":"https://careers.datadoghq.com/detail/8261937/?gh_jid=8261937","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T16:34:19Z","expires_at":"2026-11-13T16:55:38.303397Z","created_at":"2026-10-14T15:19:28.521017Z","updated_at":"2026-10-14T16:55:38.306288Z","company_name":"Datadog","company_slug":"datadog","company_logo_url":"https://www.google.com/s2/favicons?domain=datadoghq.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bed4ba83-1003-483b-ae16-2e373644bf3e"},{"id":"db835cf3-0130-489a-9931-b9d8c638a18d","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Engineer - Perception Modeling","slug":"senior-engineer-perception-modeling-3f6335e2","description":"On our Perception team, you have the opportunity to work with world-class ML engineers and research scientists, whose mission is to make self-driving vehicles a reality and to create a positive social impact. Our team works on the tech stack responsible for perceiving the dynamic scenarios, and further tracking and classifying objects around our robo-taxi. We are looking for engineers who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.\n What You'll Be Doing: \n \n Lead the architecture and development of advanced perception systems, focusing on, large-scale multi-modal foundation models, and robust knowledge generalization across vehicle generations\n Architect and scale synthetic data generation and sensor simulation capabilities to tackle long-tail edge cases, unseen off-log scenarios, and closed-loop evaluation\n Drive knowledge transfer from large teacher/foundation models to efficient onboard real-time perception models via advanced distillation and post-training techniques\n Productionize and deploy solutions onto autonomous vehicle fleets\n Provide technical leadership, mentorship, and guidance to senior and mid-level engineers on the team\n \n What We're Looking For: \n \n 3+ years of experience in Machine Learning, Computer Science, Robotics, or a related field\n Masters or Ph.D. in Machine Learning, Computer Science, Robotics, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience\n In-depth understanding of common Machine Learning and Deep Learning algorithms\n Experience with designing, training, and analyzing neural networks for at least one of the following applications: object detection, semantic/instance segmentation, visual classification, motion/gesture recognition, sensor fusion, multitask learning, multi-object tracking, and/or end-to-end perception\n Experience with deep learning frameworks such as TensorFlow or PyTorch\n Fluency in Python, including standard scientific computing libraries and Python bindings development experience\n Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods\n Excellent communication and interpersonal skills\n Experience mentoring and leading others\n \n Preferred, but not required: \n \n Proven track record in designing, training, or fine-tuning Foundation Models (e.g., Vision-Language Models, Multimodal Transformers) for autonomous driving or robotic perception\n Deep expertise in World Models, generative video/lidar prediction, scene synthesis, and sensor simulation for closed-loop evaluation\n Strong experience with Knowledge Distillation and model compression techniques to transfer capability from large offline teacher models to lightweight edge deployments\n Demonstrated experience with Synthetic Data Generation (SDG) and multi-modal automated labeling systems to scale training data quality and volume\n Publications in premier computer vision or machine learning conferences (e.g., CVPR, ICML, NeurIPS, ICCV, ECCV)\n \n  \n #LI-BP1 \n The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.  \n Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. \n Salary Range\n $172,000 — $229,000 USD \n Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more. \n Our journey is always people first. \n We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.\n Higher purpose, greater impact. \n We’re creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world diffe","salary_min":172000,"salary_max":229000,"location":"Boston, MA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["generative-ai","autonomous-vehicles","computer-vision","deep-learning","fine-tuning","robotics","pytorch","tensorflow"],"apply_url":"https://motional.com/open-positions/?gh_jid=8008804003#/8008804003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-06T17:15:40Z","expires_at":"2026-11-13T16:56:23.389669Z","created_at":"2026-10-14T15:20:30.46965Z","updated_at":"2026-10-14T16:56:23.392751Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/db835cf3-0130-489a-9931-b9d8c638a18d"},{"id":"56ebdfff-97fb-41ef-a385-6ed65f0a35ea","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Staff Applied AI Engineer - Enterprise AI Solutions","slug":"staff-applied-ai-engineer-enterprise-ai-solutions-9fe2164f","description":"About Snorkel \n Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes.  Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n The Role\n As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end.\n Main Responsibilities\n \n Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This will involve designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of Snorkel’s tooling.\n Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows.\n Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role.\n Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects.\n Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup.\n Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices.\n Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI.\n Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams.\n Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.\n Annual travel up to 25%.\n \n Preferred Qualifications\n \n B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience.\n 8+ years of customer-facing experience in the design and implementation of AI/ML solutions.\n Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow).\n Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI).\n Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement.\n Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.\n Ability to work in a fast-paced environment and balance priorities across multiple projects at once.\n \n Co","salary_min":230000,"salary_max":360000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","embeddings","pytorch","deep-learning","fine-tuning","agents","generative-ai","rag"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6204368004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-06T03:25:50Z","expires_at":"2026-11-13T16:55:33.58289Z","created_at":"2026-10-14T15:19:23.699153Z","updated_at":"2026-10-14T16:55:33.585681Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/56ebdfff-97fb-41ef-a385-6ed65f0a35ea"},{"id":"25cc098c-d5a9-4722-8570-cdb9d8c94f57","company_id":"63bced38-3605-4e57-99f3-e213b2d40bf3","title":"Data Scientist II","slug":"data-scientist-ii-cdd4036b","description":"Data Scientist II, Cohere Health, Inc., Boston, Massachusetts (Remote) \n Duties: Gather business requirements and apply trend analysis to identify actionable insights using analytic tools. Analyze healthcare claims and authorization data to identify outliers, interpret patterns, and assess trends and opportunities. Apply large language models (LLMs), stochastic optimization methods, and related technologies to support decision-making. Monitor industry trends, regulatory changes, and emerging fraud schemes to support detection strategy development, maintain methodology documentation, and present findings to leadership. Train, fine-tune, and implement LLMs and deep learning models for tasks such as anomaly detection, classification, and automated analysis of security-related or operational data. Analyze datasets to assess expected impacts and return on investment, including effects on medical expense, administrative cost, and clinical outcomes. Develop data models, algorithms, and simulations to support analytical objectives. Build visualizations and dashboards to communicate analytical findings and support business workflows.\n This is a fully remote position and may be performed from anywhere within the United States. Occasional travel to company headquarters in the U.S. for onboarding, team meetings, and company events may be required.\n Requirements:\n Must have a Master’s degree in Data Science, Statistics, Biostatistics or related field (willing to accept foreign education equivalent) and 36 months of experience as Analyst or related position analyzing datasets.\n Must possess three (3) years of experience (may be gained concurrently with above experience) in the following skills:\n \n Analyzing healthcare datasets, including EMR/EHR data, medical and pharmacy claims data, and Social Determinants of Health (SDoH) data;\n Performing data quality analysis to identify data quality issues, gaps, or inconsistencies;\n Building scalable AWS Airflow pipelines to ingest, integrate, and transform terabytes of data using Python and PySpark and AWS S3 storage, and accelerate business decision-making in AWS Sagemaker; \n Utilizing trend identification and data analysis methods such as regression analysis and outlier detection model in python, spark and sql.;\n Building and implementing models, creating algorithms, and running simulations;\n Developing Tableau visualization and partnering with product owners and stakeholders to drive enterprise-level solutions that integrate data science into business workflows; \n Developing NLP, LLMs (extractive and generative), fine-tuning, and LLM model development.\n \n Salary range is $137,000.00 to $161,000.00 per year for a 40-hour work week.\n #LI-DNI\n -\n #BI-DNI\n -","salary_min":137000,"salary_max":161000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["healthcare","nlp","fine-tuning","cloud","llm","deep-learning","data-science"],"apply_url":"https://job-boards.greenhouse.io/coherehealth/jobs/8005450003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-05T19:10:55Z","expires_at":"2026-11-13T16:56:47.541154Z","created_at":"2026-10-14T15:20:32.691553Z","updated_at":"2026-10-14T16:56:47.544068Z","company_name":"Cohere Health","company_slug":"cohere-health","company_logo_url":"https://www.google.com/s2/favicons?domain=coherehealth.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/25cc098c-d5a9-4722-8570-cdb9d8c94f57"},{"id":"6c602d86-d419-4ce2-929d-1dbc939432ed","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior Computer Vision Engineer","slug":"senior-computer-vision-engineer-29ad051c","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 Counter Intrusion MSE team develops systems that provide force protection capabilities, monitoring the perimeter of secure areas, land or sea, for approaching people, vehicles, and vessels. We live in a world where security officers are increasingly overwhelmed by sensor data feeds. Our products leverage advanced sensor fusion and autonomy to seamlessly render activity in the environment to Lattice's common operating picture. This relieves operators of our system from a ton of burden and allows our customers to get more done with fewer personnel. Increasingly, Counter Intrusion MLEs are working on projects to bring customers' existing legacy security systems into the Lattice ecosystem. Key to this effort is building scalable software solutions so that we can service many customers without requiring bespoke software for each one. The Counter Intrusion team is responsible for the development, testing, deployment, and sustainment of our family of systems. We work closely with other teams from product, engineering, sales, logistics, operations, and mission success.\n About the Role\n We are looking for a Machine Learning Engineer to apply the latest research to solve our toughest problems. This role will be responsible for owning the whole machine learning stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for perception on edge compute devices that push the boundaries of what's possible with our sensors. You will develop learning algorithms to optimize the behavior of autonomous systems. You will also be responsible for the end-to-end design, implementation, and performance of the ML stack, including the infrastructure for data collection and training. Your work will directly impact Anduril's ability to deliver cutting-edge defense technology, with the opportunity to identify and develop novel ML applications across our product portfolio.\n Responsibilities\n \n Propose and prototype innovative solutions to solve real-world problems, leveraging the latest state-of-the-art techniques in the field\n Develop and maintain core ML pipelines\n Train and deploy deep learning models for real-time applications\n Collaborate cross-functionally with camera, systems and labeling teams\n Curate datasets for evaluating performance and comparing performance trends over time\n Provide technical mentorship to other junior ML engineers\n \n Required Qualifications\n \n MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision\n BS in Computer Science, Machine Learning, Electrical Engineering, or related field\n 6+ years of experience developing, benchmarking and optimizing ML algorithms on large-scale datasets\n Strong Deep Learning and CV background\n Proficiency in C++ development in a Linux environment\n Experience with Python development and deep learning frameworks such as PyTorch, JAX and TensorFlow\n Experience deploying models with TensorRT and ONNX\n Optimize on-device inference and vision kernels across CPU/GPU/NPU\n Track record of developing and deploying CV models from R\u0026D to production\n Experience writing and maintaining automated continuous integration tests\n Knowledge of system profiling and tuning for latency, memory and power efficiency\n Ability to conduct experiments, ablation studies and create highly detailed reports\n Eligible to obtain and maintain a U.S. Secret security clearance\n \n Preferred Qualifications\n \n Experience in one or more of the following:\n \n Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic Change Detection, Depth Estimation, Model Pruning and Compression\n \n Experience in one or more of the following:\n \n Visual Odometry, SLAM, Multi-view Geometry, Camera Models, RGB-D and LIDAR Sensor Fusion, Optical Flow\n \n Experience troubleshooting and analyzing remotely deployed software systems\n 1 year of experience in a technical leadership role\n US Hourly Range \n $220,000 — $292,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Hi","salary_min":220000,"salary_max":292000,"location":"Irvine, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["jax","computer-vision","deep-learning","tensorflow","robotics","pytorch","cloud","payments"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5256999007?gh_jid=5256999007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-05T17:08:54Z","expires_at":"2026-11-13T16:57:16.198459Z","created_at":"2026-10-14T15:21:01.365645Z","updated_at":"2026-10-14T16:57:16.201756Z","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/6c602d86-d419-4ce2-929d-1dbc939432ed"},{"id":"e0be16b1-242b-4a96-b22e-736f0755cae8","company_id":"5a1ac926-3bb4-40bb-b952-7dc959ae1820","title":"Tech Lead Manager, Machine Learning, Growth and Marketing   ","slug":"tech-lead-manager-machine-learning-growth-and-marketing-527e3a43","description":"About the Role \n Chime’s Data Science and Machine Learning team is building models, services, and platforms that transform how millions of users manage and grow their financial lives. We are looking for a hands-on Tech Lead Manager with deep technical expertise in machine learning and data science, particularly within the Growth and Marketing domain. Beyond technical proficiency, we value creativity, user empathy, and strong collaboration. \n As a Tech Lead Manager within our Growth and Marketing team, you will lead a talented group of data scientists and machine learning engineers to develop innovative growth and marketing models. These models will provide critical insights into acquiring, retaining and growing Chime members, broaden access to credit, and ensure financial inclusivity. You will play a pivotal role in creating innovative, ground-up products while driving the development of cutting-edge acquisition and retention models and solutions. If you are passionate about marketing, growth, customer acquisition and retention models, this role could be a great fit for you. \n In this role, you can expect to \n \n Lead and inspire a high-performing team of data scientists and ML engineers, ensuring the successful development and deployment of machine learning solutions for customer acquisition, conversion and retention. \n Drive strategic direction for ML initiatives in marketing, engagement, and growth by identifying opportunities where AI/ML can optimize our customer funnel. \n Oversee the end-to-end development of machine learning models such as lifetime value prediction, churn risk modeling, customer segmentation, marketing attribution, referral recommendations, and personalized communications. \n Collaborate cross-functionally with marketing, product, growth, and engineering teams to align machine learning initiatives with business objectives. \n Leverage transactional and behavioral data to enhance customer targeting, optimize acquisition spend, and improve retention strategies. \n Establish ML best practices, including model development, validation, deployment, and monitoring, ensuring scalability and business impact. \n Advocate for a data-driven culture, partnering with business leaders to drive strategic decisions through experimentation and predictive analytics. \n Stay ahead of industry trends, bringing cutting-edge AI/ML techniques into our marketing and growth strategies. \n \n To thrive in this role, you have \n \n 7+ years of experience developing machine learning models for marketing and growth, from inception to production, with a focus on customer acquisition, engagement, and retention. \n 5+ years of experience leading data science teams, with a proven track record of mentoring, coaching, and driving impactful machine learning solutions. \n Strong expertise in marketing and growth analytics, including experience with customer segmentation, LTV modeling, churn prediction, referral systems, and multi-touch attribution. \n Deep understanding of AI/ML techniques, including classification, clustering, reinforcement learning, optimization, deep learning, and NLP for customer engagement. \n Hands-on experience deploying machine learning models in real-world production environments, integrating with marketing tech stacks and growth platforms. \n Strong product intuition with the ability to work iteratively in a fast-paced, cross-functional environment. \n M.S. or Ph.D. in Machine Learning, Computer Science, Statistics, or a related STEM field. \n Proficiency in Python and SQL, with experience in building ML pipelines and wrangling large-scale data. \n Experience with modern ML and data engineering technologies, such as AWS, Kafka, Airflow, Redis, MySQL, Postgres, Spark, Snowflake, Looker. \n Exceptional communication and stakeholder management skills, with the ability to partner effectively with marketing, growth, product, and engineering teams. \n \n #LI-DA1 #LI-Onsite \n Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.\n Wage Notice\n $199,000 — $275,000 USD \n A little about us \n At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. \n We're a team of problem solvers, dreamers, and builders with one ","salary_min":199000,"salary_max":275000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["nlp","deep-learning","payments","reinforcement-learning","data-engineering","machine-learning"],"apply_url":"https://boards.greenhouse.io/chime/jobs/8864214002?gh_jid=8864214002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-02T18:01:52Z","expires_at":"2026-11-13T17:03:12.47807Z","created_at":"2026-10-14T15:25:16.005996Z","updated_at":"2026-10-14T17:03:12.481159Z","company_name":"Chime","company_slug":"chime","company_logo_url":"https://www.google.com/s2/favicons?domain=chime.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e0be16b1-242b-4a96-b22e-736f0755cae8"},{"id":"4939555c-c4ef-4776-b87e-a2fdd8a1f17c","company_id":"099a8aa7-a1bc-4a90-aa8d-f59f677b925a","title":"Senior AI Software Engineer, Perception","slug":"senior-ai-software-engineer-perception-36ebc12d","description":"Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.\n  \n Agility Robotics builds Digit, the world's first commercially deployed humanoid robot — already at work in real warehouses and manufacturing facilities today. Digit has proven itself in structured work cells, and now we're pushing beyond them: into open floors, shared aisles, and dynamic spaces where people, forklifts, and other robots are all moving at once. That shift raises the bar for perception dramatically — Digit needs to reliably understand and react to environments that are no longer predictable or controlled. \n That means perception isn't just about capability — it's about trust. Every person Digit works near is counting on our perception systems to see them, understand them, and never get it wrong, whether Digit is in a fixed work cell or navigating a busy, ever-changing facility. We're looking for a Senior AI Software Engineer, Perception to own the design and implementation of the algorithms that let Digit perceive its surroundings and stay safe as we take on these more dynamic, less constrained environments. \n What You'll Do \n \n Design, develop, and deploy perception algorithms (e.g., human detection algorithm) that enable safety and efficiency, defining how Digit perceives and reasons about humans and hazards as it expands from structured work cells into open, dynamic environments \n Drive adoption of state-of-the-art perception models by evaluating emerging research and technology and deciding what's worth building into future robot architectures \n Promote best practices in model design, implementation and testing to deliver high-quality, scalable software \n Optimize deep neural networks and associated data pipelines to run efficiently on embedded systems (e.g., model structure optimization, CUDA inference etc.) \n Set standards for verification and validation of ML-based perception models, especially for rare and safety-critical scenarios \n Collaborate across navigation, controls, and hardware teams to ensure the perception model serves the whole robot \n \n What You Bring \n \n 5+ years of experience in machine learning/perception for robotics \n Master's or Ph.D. in Artificial Intelligence, Robotics, Computer Science, or a related discipline, with a strong foundation in machine learning, robotics, and intelligent systems \n Demonstrated experience building ML/perception systems for safety-critical or safety-rated contexts — human detection, automotive, robotics, or a comparable regulated domain \n Deep expertise in convolutional neural networks, multi-object tracking, human detection, data association, supervised learning, and pose estimation, with strong intuition for where these approaches break down in unpredictable, real-world conditions \n Experience designing and optimizing algorithms for efficient execution across CPU and GPU architectures \n Experience with MLOps, including data annotation services, data storage, model evaluation tools, and model deployment \n Publications in the field (CVPR, ICCV, RSS, ICRA preferred) \n \n Nice to Haves \n \n Experience designing and implementing perception systems for humanoid or legged robots specifically \n Experience building systems based on multiple sensor modalities including camera, lidar, infrared camera.  \n Knowledge in traditional geometric computer vision and sensor hardware etc. \n \n  \n \n  \n This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices. \n The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future. \n Anticipated Salary Range\n $197,000 — $307,000 USD \n In addition to base pay, our competitive total rewards package consists of the following for full-time employees: \n \n 401(k) Plan:   Includes a 6% company match.\n Equity:   Company stock options.\n Insurance Coverage:   100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.\n Benefit Start Date:   Eligible for benefits on your first day of employment.\n Well-Being Support:   Employee Assistance Program (EAP).\n Time Off: \n \n Exempt Employees:   Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.\n Non-Exempt Employees:   10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.\n \n On-Site Perks:   Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.\n Parental Leave:   ","salary_min":197000,"salary_max":307000,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","computer-vision","gpu","data-pipeline","robotics","mlops"],"apply_url":"https://www.agilityrobotics.com/about/job-post?gh_jid=6210999004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-30T16:15:10Z","expires_at":"2026-11-13T16:59:26.118513Z","created_at":"2026-10-14T15:22:58.177037Z","updated_at":"2026-10-14T16:59:26.121355Z","company_name":"Agility Robotics","company_slug":"agility-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=agilityrobotics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4939555c-c4ef-4776-b87e-a2fdd8a1f17c"},{"id":"ec278267-477d-4688-a758-54877ad70f37","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Machine Learning Engineer II - Learned Planning (Reinforcement Learning)","slug":"machine-learning-engineer-ii-learned-planning-reinforcement-learning-6785c795","description":"About the Company  \n At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. \n A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.  Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. \n Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. \n Meet the Team:   As a Machine Learning Engineer II – Learned Behaviors, you will help develop and deploy  behavior models that power decision-making for autonomous trucks. Working closely with teams across perception, prediction, planning, and safety, you will contribute to learned behavior modules that enable safe, efficient, and human-like driving in real-world freight operations.    This role focuses on building, validating, and improving machine learning models and infrastructure that support learned behavior systems within the autonomy stack.    What You’ll Do  \n \n Develop and train machine learning models for learned behavior systems, including approaches such as behavior cloning, imitation learning, and reinforcement learning.\n Implement production-quality ML code to support model training, evaluation, and inference within the autonomy stack.\n Analyze model performance, identify failure modes, and propose improvements to increase robustness and generalization across scenarios.\n Contribute to model training pipelines and data workflows, curating behavior datasets from simulation, fleet logs, and on-vehicle data.\n Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate learned behavior models across diverse driving environments.\n Help integrate learned behavior models into simulation and testing workflows, enabling faster iteration and more comprehensive validation.\n Support the development of tooling and infrastructure that improves experimentation speed, reproducibility, and model iteration.\n Contribute to technical discussions around model architecture and training strategies within the team. \n \n What You’ll Need to Succeed  \n \n Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 4+ years of industry experience, or a Master’s degree with 2+ years of experience. \n Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments.\n Strong programming skills in Python and PyTorch, with experience writing production-quality ML code.\n Experience training and evaluating machine learning models using large datasets and scalable compute environments.\n Understanding of ML architectures used in autonomy systems, such as transformers, graph neural networks, or sequence models.\n Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines.\n Ability to collaborate with cross-functional teams to integrate ML models into larger software systems. \n \n Bonus Points!  \n \n Experience working in autonomous driving, robotics, or simulation-based training environments.\n Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray).\n Experience working with simulation environments or large-scale behavior datasets.\n Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems.\n Experience deploying ML models into production or real-world robotics systems. \n \n Perks of Being a Full-time Torc’r   Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:     \n \n A competitive compensation package that includes a bonus component and stock options\n 100% paid medical, dental, and vision premiums for full-time employees\n 401K plan with a 6% employer match\n Flexibility in schedule and generous paid vacation (available immediately after start date)\n AD+D and Life Insurance \n \n At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.  Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. \n For this position, we are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United S","salary_min":153200,"salary_max":183800,"location":"Ann Arbor, MI","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["deep-learning","distributed-systems","payments","reinforcement-learning","agents","autonomous-vehicles","pytorch","robotics"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8852888002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-29T21:15:57Z","expires_at":"2026-11-13T16:56:17.74727Z","created_at":"2026-10-14T15:20:25.93453Z","updated_at":"2026-10-14T16:56:17.749834Z","company_name":"Torc Robotics","company_slug":"torc-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=torc.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ec278267-477d-4688-a758-54877ad70f37"}],"page":1,"per_page":20,"total":655,"total_is_exact":true,"total_pages":33}