{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","employer_pilot_url":"https://aidevboard.com/verified-interview-pilot","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"candidate_resume_action":{"application_authorized":false,"candidate_charge":0,"endpoint":"https://aidevboard.com/api/v1/candidate/resume-preview","job_id_json_path":"jobs[].id","method":"POST","preview_requires_identity":false,"required_body_fields":["job_id","evidence_bullets"],"requires_explicit_human_review":true,"saved_artifact_protocol":"mcp","saved_artifact_requires_verified_human":true,"saved_artifact_tool":"compile_job_specific_resume","search_requires_identity":false,"status":"available_after_candidate_selects_job","submission_performed":false,"uses_candidate_verified_evidence":true},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"385357c5-623e-4db0-baf5-06182c0f554f","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Staff Machine Learning Engineer, Emergency Trajectory Models","slug":"staff-machine-learning-engineer-emergency-trajectory-models-f0038f44","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role  \n As a Staff Machine Learning Engineer in Wayve's AV Core organization, you will lead the technical direction and delivery of a learned emergency trajectory model for low-frequency, high-consequence maneuvers such as evasive steering and emergency braking. You will take the programme from problem definition through modelling, evaluation, integration, and evidence for deployment.\n Emergency maneuvers are rare, high-consequence events that place unusual demands on data, modelling, and validation. The hard problem is not simply to train another trajectory head: it is to define the operating envelope of a specialist model, what evidence shows that it improves outcomes without introducing new failure modes, and how it integrates with the general driving model and surrounding system. You will lead that work across AV Core and with partners across simulation, evaluation, safety, and product engineering.\n  \n Key responsibilities \n \n Set the technical strategy and roadmap for the emergency trajectory model, including its behavioral scope, operating envelope, system interfaces, and measurable acceptance criteria.\n Design and train trajectory-generating policies using the methods best supported by evidence, including behaviour cloning, reinforcement learning, or other sequential decision-making approaches.\n Build a data strategy for rare emergency cases, combining fleet data, targeted mining, simulation, augmentation, and reweighting while controlling coverage gaps and unintended behavior.\n Create rigorous open-loop and closed-loop evaluations for collision avoidance, evasive steering, emergency braking, recovery, robustness, latency, and regressions in nominal driving.\n Lead integration into the shared driving stack, align technical decisions across teams, and raise the bar through architecture reviews, mentoring, and clear communication of risks, trade-offs, and evidence.\n \n About you   \n In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.  \n  \n Essential  \n \n A track record of staff-level technical leadership: setting direction for ambiguous machine learning programmes, aligning multiple teams, and carrying work from research through production deployment.\n Deep expertise developing learned trajectory-generation or policy models for embodied systems, including architecture design, objective design, training, and empirical validation.\n Hands-on experience with behaviour cloning, reinforcement learning, or related methods, including objective design, distribution shift, robustness, and closed-loop failure analysis.\n Strong machine learning engineering skills in Python and PyTorch, with experience building reproducible training and evaluation systems on large, heterogeneous datasets.\n Exceptional technical judgement and communication: able to make safety-relevant trade-offs explicit, define the evidence needed for decisions, and lead without relying on formal authority.\n \n  \n Desirable  \n \n Experience applying learned models in autonomous driving or robotics, with strong understanding of motion planning, vehicle dynamics, control, or collision avoidance.\n Experience with specialist, fallback, redundant, mixture-of-experts, or model-routing architectures and the interfaces used to select between them.\n Experience mining, generating, or evaluating rare events using simulation and fleet or real-world data.\n Experience deploying learned policies under real-time latency, reliability, and compute constraints; proficiency in C++, CUDA, or systems optimisation.\n Experience with multimodal, transformer-based, diffusion-based, or other generative trajectory or policy models.\n \n This is a full-time role based in our office in Sunnyvale.  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and lear","salary_min":336400,"salary_max":370300,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","gpu","robotics","autonomous-vehicles","generative-ai","pytorch","machine-learning"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8747065002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T18:15:27Z","expires_at":"2026-09-29T13:43:29.618384Z","created_at":"2026-08-25T18:31:14.484268Z","updated_at":"2026-08-30T13:43:29.754954Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/385357c5-623e-4db0-baf5-06182c0f554f"},{"id":"0de3bf04-c0e7-4cad-808a-3b266b247482","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"MSE, Vehicle Software, RUST","slug":"mse-vehicle-software-rust-6adc91e9","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 Air Dominance \u0026 Strike (AD\u0026S) is responsible for autonomous robotics systems like the Fury unmanned fighter jet and the Barracuda family of advanced effects. The AD\u0026S Vehicle Software team is responsible for the software running on these systems. Our senior software engineers collaborate with other engineering disciplines to develop software for vehicle control, networking, sensor integration, and telemetry. We are looking for engineers excited to build the foundational vehicle software stack that supports the wide range of AD\u0026S initiatives, from early concept simulation to first flight to live operations to large scale fleet management.\n REQUIRED QUALIFICATIONS \n \n Eligible to obtain and maintain an active U.S. Top Secret security clearance\n BS, MS, or PhD in Computer Science, Software Engineering, Mathematics, Physics, or related field.\n 3+ years of production-grade Rust and/or C++ experience in a Linux development environment\n Experience building software solutions involving significant amounts of data processing and analysis\n Ability to quickly understand and navigate complex systems and established code bases\n A desire to work on critical software that has a real-world impact\n Travel up to 20% of time to build, test, and deploy capabilities in the real world\n \n PREFERRED QUALIFICATIONS \n \n Strong background with focus in Physics, Mathematics, and/or Motion Planning to inform modeling \u0026 simulation (M\u0026S) and physical systems\n Developing and testing multi-agent autonomous systems and deploying in real-world environments.\n Feature and algorithm development with an understanding of behavior trees.\n Developing software/hardware for flight systems and safety critical functionality.\n Distributed communication networks and message standards\n Knowledge of military systems and operational tactics\n US Salary Range\n $166,000 — $220,000 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. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:\n \n \n No Financial Requests:  Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.\n Please always verify communications: \n \n Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.\n Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com . \n \n \n Exercise Caution with Unsolicited Outreach:  If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.\n \n What to Do If You Suspect Fraud:  Should you ","salary_min":166000,"salary_max":220000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["computer-vision","gpu","agents","robotics","payments","cloud","rust"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5218934007?gh_jid=5218934007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T19:48:46Z","expires_at":"2026-09-29T13:37:18.257375Z","created_at":"2026-08-25T18:28:19.086086Z","updated_at":"2026-08-30T13:37:18.392192Z","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/0de3bf04-c0e7-4cad-808a-3b266b247482"},{"id":"c4bf12e8-d3d5-4579-ad68-ed7770dc9043","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Staff Software Engineer, Vehicle Software, C++","slug":"staff-software-engineer-vehicle-software-c-8ad6a6d0","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 Air Dominance \u0026 Strike (AD\u0026S) is responsible for autonomous robotics systems like the Fury unmanned fighter jet and the Barracuda family of advanced effects. The AD\u0026S Vehicle Software team is responsible for the software running on these systems. Our Staff Software Engineers collaborate with other engineering disciplines to develop software for vehicle control, networking, sensor integration, and telemetry. We are looking for engineers excited to build the foundational vehicle software stack that supports the wide range of AD\u0026S initiatives, from early concept simulation to first flight to live operations to large scale fleet management.\n REQUIRED QUALIFICATIONS \n \n Eligible to obtain and maintain an active U.S. Top Secret security clearance\n BS, MS, or PhD in Computer Science, Software Engineering, Mathematics, Physics, or related field.\n 9+ years of production-grade C++ and/or Rust experience in a Linux development environment\n Experience building software solutions involving significant amounts of data processing and analysis\n Ability to quickly understand and navigate complex systems and established code bases\n A desire to work on critical software that has a real-world impact\n Travel up to 30% of time to build, test, and deploy capabilities in the real world\n \n PREFERRED QUALIFICATIONS \n \n Strong background with focus in Physics, Mathematics, and/or Motion Planning to inform modeling \u0026 simulation (M\u0026S) and physical systems\n Developing and testing multi-agent autonomous systems and deploying in real-world environments.\n Feature and algorithm development with an understanding of behavior trees.\n Developing software/hardware for flight systems and safety critical functionality.\n Distributed communication networks and message standards\n Knowledge of military systems and operational tactics\n US Salary 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. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:\n \n \n No Financial Requests:  Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.\n Please always verify communications: \n \n Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.\n Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com . \n \n \n Exercise Caution with Unsolicited Outreach:  If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.\n \n What to Do If You Suspect Fraud:  Should you e","salary_min":220000,"salary_max":292000,"location":"Boston, MA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["payments","agents","robotics","gpu","computer-vision","cloud","c++"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5218845007?gh_jid=5218845007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T18:30:29Z","expires_at":"2026-09-29T13:37:29.937413Z","created_at":"2026-08-25T18:28:19.650421Z","updated_at":"2026-08-30T13:37:30.072464Z","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/c4bf12e8-d3d5-4579-ad68-ed7770dc9043"},{"id":"567e9ccc-275b-41f9-bbbb-2f9a2837b11e","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Robotics Engineer II","slug":"robotics-engineer-ii-db033019","description":"May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. \n Essential Responsibilities \n \n Train, Integrate and Test Machine Learning models for on-vehicle Autonomy software\n Optimize and Monitor on-vehicle software for maximum reliability and minimum latency\n Coordinate and execute on-vehicle tests to validate performance of Autonomous Vehicle software in real-world scenarios\n Diagnose and root-cause issues reported by commercial operations through the May Field Response process\n Design and oversee data collection strategies to address ML model deficiencies \n Develop tools and visualizations to enable support engineers to analyze performance of behavior and control subsystems from field data\n \n Qualifications and Experience \n Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience: \n Required \n \n 2+ years experience with robotics software for physical systems in a commercial environment\n Bachelor's degree in Robotics, Computer Science, Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation (e.g. physics, aerospace engineering)\n Basic understanding of ML model concepts such as training, architectures, and data selection\n Functional understanding of lidar, camera and/or radar perception systems and their hardware interfaces\n Strong programming skills in C/C++/Python in a Linux environment\n Functional proficiency with Software concepts such as memory management, threading, databases and networking\n Familiarity with standard development tools such as git, valgrind, and gdb\n \n Desirable \n \n Familiarity with common Perception, Planning and Foundation model concepts in Autonomous Driving.\n Experience deploying ML models to resource-constrained hardware\n Experience with CUDA and GPU processing techniques\n Proficiency with hard example mining, active learning or dataset composition techniques\n Experience calculating metrics for and evaluating autonomous vehicle models\n Experience building training and evaluation pipelines for large data (\u003e100TB) or large model (\u003e100GB) applications\n \n Physical Requirements \n \n Standard office working conditions which includes but is not limited to:\n \n Prolonged sitting\n Prolonged standing\n Prolonged computer use\n \n \n \n Travel required? -  Minimal: 1%-10%\n \n \n \n \n \n \n \n \n Benefits and Perks \n \n Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. \n Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.\n Rich retirement benefits, including an immediately vested employer safe harbor match.\n Generous paid parental leave as well as a phased return to work. \n Flexible vacation policy in addition to paid company holidays.\n Total Wellness Program providing numerous resources for overall wellbeing   \n \n Don’t meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we’re committed to building a diverse, inclusive, and authentic workforce, so if you’re excited about this role but your previous experience doesn’t align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May.\n Want to learn more about our culture \u0026 benefits? Check out our  website ! \n May Mobility is an equal opportunity employer.  All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis.   Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with May Mobility to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions","salary_min":130000,"salary_max":155000,"location":"Ann Arbor, MI","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["generative-ai","gpu","healthcare","autonomous-vehicles","robotics"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8734496002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T20:12:21Z","expires_at":"2026-09-29T13:47:54.420086Z","created_at":"2026-08-25T18:33:07.014049Z","updated_at":"2026-08-30T13:47:54.550395Z","company_name":"May Mobility","company_slug":"may-mobility","company_logo_url":"https://www.google.com/s2/favicons?domain=maymobility.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/567e9ccc-275b-41f9-bbbb-2f9a2837b11e"},{"id":"e83f9b8b-565f-4a94-b2f4-03b79a6f7843","company_id":"2114efab-ea67-411b-bfb8-7899153105f3","title":"Member of Technical Staff, Site Reliability Engineer","slug":"member-of-technical-staff-site-reliability-engineer-369fc8ef","description":"Overview\n\nInferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.\n\nAbout the Role\n\nWe're looking for a Site Reliability Engineer to help make vLLM-powered inference systems reliable, observable, and operationally simple at production scale. This role is for someone who thinks about failure before launch, designs systems that are easier to operate, and knows how to turn incidents into durable improvements rather than one-off fixes.\n\nYou'll work across engineering and infrastructure to define SLOs, improve monitoring and alerting, strengthen incident response, drive post-mortems, and reduce operational risk before it reaches users. Your work will directly impact the reliability, availability, and production readiness of the systems powering AI inference at scale.\n\n\n\nSkills and Qualifications\n\nMinimum qualifications:\n\n - Bachelor's degree or equivalent experience in computer science, engineering, systems, infrastructure, or similar.\n\n - Strong experience operating production systems with meaningful traffic, user impact, or infrastructure criticality.\n\n - Deep understanding of SLOs, SLIs, error budgets, alerting, incident response, and post-mortem processes.\n\n - Experience live-fighting major production incidents, including mitigation, root cause analysis, escalation, and follow-through on prevention work.\n\n - Strong Linux, networking, systems debugging, observability, and distributed systems fundamentals.\n\n - Ability to design operationally simple systems and identify likely failure modes before launch.\n\n - Strong programming or scripting ability in Python, Go, Bash, or similar for automation, tooling, and reliability improvements.\n\nPreferred qualifications:\n\n - Experience supporting ML infrastructure, inference systems, GPU workloads, Kubernetes-based platforms, or high-scale backend services.\n\n - Experience building or improving observability systems using metrics, logs, traces, dashboards, alerts, and runbooks.\n\n - Experience with Kubernetes, Docker, Terraform, cloud infrastructure, service meshes, CI/CD systems, or production deployment platforms.\n\n - Experience driving incident review culture, post-mortem processes, reliability reviews, and prevention-oriented engineering work.\n\n - Ability to partner with engineering teams to improve service design, release safety, capacity planning, and operational readiness.\n\nBonus points if you have:\n\n - Owned reliability for high-throughput, latency-sensitive, or mission-critical production systems.\n\n - Supported AI inference, model serving, GPU clusters, ML platforms, or distributed serving infrastructure.\n\n - Built automation that reduced toil, improved recovery time, or prevented repeat incidents.\n\n - Led incident response for severe outages with clear communication across engineering and leadership.\n\n - Created practical SLOs, dashboards, alerts, runbooks, or release gates that improved production reliability.\n\n\n\nLogistics\n\n - Location: This role is based in San Francisco, California. Will consider remote in the US for exceptional candidates.\n\n - Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.\n\n - Visa sponsorship: We sponsor visas on a case-by-case basis.\n\n - Benefits: We offers generous health, dental, and vision benefits as well as 401(k) company match.","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","mlops","gpu","cloud","distributed-systems","devops","research"],"apply_url":"https://jobs.ashbyhq.com/inferact/ad992ead-2a9a-4694-8fca-0504354548cd/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T18:25:22.552Z","expires_at":"2026-09-29T13:41:27.521095Z","created_at":"2026-08-25T18:30:22.617589Z","updated_at":"2026-08-30T13:41:27.654002Z","company_name":"Inferact","company_slug":"inferact","company_logo_url":"https://www.google.com/s2/favicons?domain=inferact.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e83f9b8b-565f-4a94-b2f4-03b79a6f7843"},{"id":"90971ca5-fcc8-4b69-835c-9a462afd1f5e","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Software Engineer II, MLOps Framework","slug":"software-engineer-ii-mlops-framework-6090a7e5","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.   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.   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   \n As a Software Engineer on the ML Ops Framework \u0026 Conversion team, you will own the pipelines that take models from research to production on edge hardware, including model conversion, compilation, benchmarking, and release. Our team is comprised of engineers with deep expertise in ML and RL frameworks, embedded systems, and autonomous driving — united by a focus on getting models from development into the real world reliably and at scale. The ML Ops Framework \u0026 Conversion team is responsible for the full model conversion process — from architecting TensorRT pipelines to maintaining the model release registry across platforms. In this role, you will work closely with perception and safety teams to ensure every model that ships meets strict latency and accuracy requirements for autonomous trucking. \n What You’ll Do   \n \n Architect and implement model conversion and compilation pipelines using tools such as ONNX, TensorRT, and torch.compile for deployment on edge devices (e.g., NVIDIA Orin).\n Maintain and evolve the model release registry, ensuring traceability and reproducibility across model versions and target platforms.\n Perform rigorous latency benchmarking and model quality parity evaluations to validate that deployed models meet safety-critical performance requirements.\n Compare metrics across platforms to verify accuracy and latency compliance before release.\n Communicate and collaborate with model development teams and broader stakeholders, ensuring your findings translate into reliable, actionable outcomes across the organization.\n \n What You’ll Need to Succeed   \n \n Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 4+ years of experience or;\n Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 0-3+ years of experience.\n Extensive experience with model conversion and compilation pipelines (ONNX, TensorRT, torch.compile) and performing rigorous latency benchmarking and quality parity validation.\n Hands-on experience deploying and testing models on edge hardware (e.g., NVIDIA Orin or similar embedded platforms).\n Experience maintaining a model release registry in a production environment.\n Ability to compare and interpret performance metrics across hardware platforms to validate models against strict latency and accuracy requirements.\n \n Bonus Points \n \n Expertise in model quantization (PTQ, QAT) and mixed-precision inference (INT8, FP8, FP4, BF16/FP16).\n Experience releasing multi-target models across heterogeneous platforms.\n Familiarity with SOTA autonomous driving perception algorithms — temporal 3D object detection, BEV, 3D Occupancy Networks — and multi-modal sensor fusion (vision, LiDAR, radar).\n C++ and/or CUDA kernel development.\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 \n \n 100% paid medical, dental, and vision premiums for full-time employees   \n \n \n 401K plan with a 6% employer match   \n \n \n Flexibility in schedule and generous paid vacation (available immediately after start date)   \n \n \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 Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dep","salary_min":139000,"salary_max":166800,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["mlops","computer-vision","gpu","robotics","payments","autonomous-vehicles"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8728727002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T16:09:33Z","expires_at":"2026-09-29T13:36:08.277033Z","created_at":"2026-08-25T18:27:50.579783Z","updated_at":"2026-08-30T13:36:08.417728Z","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/90971ca5-fcc8-4b69-835c-9a462afd1f5e"},{"id":"6aabed50-4dbf-497c-bf63-c12df13dba87","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Lead Machine Learning Engineer","slug":"lead-machine-learning-engineer-d35ab649","description":"May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. \n We are seeking Machine Learning Leaders in the Autonomous Vehicle domain. As part of our team, you will play a critical role in enhancing May’s Machine Learning capabilities both on and off the vehicle, in a commercial large-scale environment with high standards of quality.\n Essential Responsibilities \n \n Design, train and evaluate state of the art models for May’s autonomous driving, simulation and ML Platform stack.\n Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems.  \n Lead small teams of cross functional Engineers beyond the state of the art.\n Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale.\n \n Skills and Abilities \n Success in this role typically requires the following competencies:\n \n Direct experience architecting \u0026 training VLA, MMLM, or Generative World Models for commercial-scale applications\n Experience composing, processing and characterizing large (\u003e100TB) multi-modal datasets\n Experience analyzing and addressing long-tail failure cases in large models\n Experience leading teams of 2-3 Engineers and communicating technical details to interdisciplinary leadership.\n \n Qualifications and Experience \n Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:\n Required \n \n Extensive practical experience in one of the following domains:\n \n Vision Language Action Models\n Generative World Models\n Foundation Models in Robotics\n Data Centric AI\n \n A minimum of 4 years of industry experience working on commercial robotics systems.\n A minimum of 1 year mentoring ML Engineers in a commercial or lab environment.\n Master’s degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation.\n Practical experience handling the “Long Tail” problem in Machine Learning.\n Strong programming skills in Python/PyTorch in a Linux environment.\n Functional understanding of LiDAR, Camera and Radar processing techniques.\n \n Desirable \n \n PhD and/or published research in the described specialty domains.\n Familiar with common post-training techniques.\n Experience deploying models to resource constrained and edge hardware\n Functional understanding of C/C++/CUDA memory and threading models.\n \n Physical Requirements \n \n Standard office working conditions which includes but is not limited to:\n \n Prolonged sitting\n Prolonged standing\n Prolonged computer use\n \n Travel required? -  Low: 5%-10%\n \n \n \n \n \n \n \n \n Benefits and Perks \n \n Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. \n Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.\n Rich retirement benefits, including an immediately vested employer safe harbor match.\n Generous paid parental leave as well as a phased return to work. \n Flexible vacation policy in addition to paid company holidays.\n Total Wellness Program providing numerous resources for overall wellbeing   \n \n Don’t meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we’re committed to building a diverse, inclusive, and authentic workforce, so if you’re excited about this role but your previous experience doesn’t align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May.\n Want to learn more about our culture \u0026 benefits? Check out our  website ! \n May Mobility is an equal opportunity employer.  All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual ","salary_min":220000,"salary_max":270000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["healthcare","autonomous-vehicles","generative-ai","robotics","pytorch","gpu","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8730957002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T19:14:18Z","expires_at":"2026-09-29T13:47:53.465471Z","created_at":"2026-08-25T18:33:06.96684Z","updated_at":"2026-08-30T13:47:53.592694Z","company_name":"May Mobility","company_slug":"may-mobility","company_logo_url":"https://www.google.com/s2/favicons?domain=maymobility.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6aabed50-4dbf-497c-bf63-c12df13dba87"},{"id":"e162808c-df72-4c08-9993-0438f336d9ac","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Staff AI Infrastructure Engineer","slug":"staff-ai-infrastructure-engineer-f1e0827b","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM   \n The Air Dominance \u0026 Strike team at Anduril develops aerial and multi-domain robotic systems. The team is responsible for taking products like Fury (unmanned fighter jet) and Barracuda (air-breathing cruise missile) from concept to product. The team also develops Lattice for Mission Autonomy, Anduril’s premier software platform that enables masses of Fury, Barracuda, and other first and third party robots to collaborate across various missions. We work in close coordination with specialist teams like Perception, Motion Planning, Hardware, and Test Engineering to solve some of the hardest problems facing our customers. We are looking for software engineers and roboticists excited about creating a powerful autonomy software stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications.   \n ABOUT THE JOB   \n We are looking for a founding  Staff AI Infrastructure Engineer  to architect, build, and scale the end-to-end machine learning platform that powers Anduril’s autonomous systems.    \n As a Staff Engineer, you will own the technical roadmap for our ML platform. You will build the robust infrastructure, MLOps tooling, and systems architecture required to train, evaluate, host, and serve complex AI models (including LLMs, computer vision, and RL agents) in both cloud environments and air-gapped, offline tactical edge networks. You will be a force multiplier for our AI Research Scientists, optimizing their experimentation velocity and managing the lifecycle of terabytes of multi-modal sensor and simulation data. Over time, you will help recruit, mentor, and expand this infrastructure engineering team.   \n WHAT YOU’LL DO   \n \n Design, build, and maintain our foundational training, orchestration, and experimentation infrastructure to support state-of-the-art model development. \n Actively identify, measure, and eliminate bottlenecks in the ML research lifecycle. Build highly automated tools for hyperparameter tuning, model profiling, and experimentation tracking.\n Design and scale robust, high-performance ETL pipelines capable of processing terabytes of multi-modal data (video, camera feeds, radar, flight telemetry, and simulation logs) captured from physical assets and test sites.\n Architect high-throughput, low-latency model serving frameworks optimized for both scalable cloud environments and air-gapped, resource-constrained tactical edge environments. Build CI/CD pipelines for ML models with automated validation, canary deployments, and rollback capabilities.\n Build robust, automated pipelines for continuous evaluation, model validation, and reinforcement learning alignment loops (RLHF/DPO) to guarantee model safety and predictability in high-stakes environments.\n Work closely with AI Researchers, Computer Vision teams, and platform engineers to design unified infrastructure standards across the company's autonomous systems programs.   \n \n REQUIRED QUALIFICATIONS   \n \n 7+ years of software engineering experience with a proven track record of designing, building, and operating production-scale machine learning systems and platforms (MLOps). \n Proficient in Python, Go, C++, or similar backend languages. Deep understanding of ML systems design, memory management, and distributed computing.\n Deep experience with containerized deployments (Docker, Kubernetes), GPU scheduling/orchestration, and distributed training frameworks (e.g., PyTorch Distributed, Ray, Slurm, or Megatron-LM).\n Hands-on experience building distributed data pipelines (ETL) and managing massive datasets (terabytes of unstructured/multi-modal sensor data).\n Experience setting technical direction, leading complex system migrations, and mentoring senior engineers.\n Eligible to obtain and maintain an active U.S. Top Secret security clearance.   \n \n PREFERRED QUALIFICATIONS   \n \n Experience building and running ML infrastructure, model serving, or software registries within secure, air-gapped, or highly regulated environments (e.g., IL5/IL6, GovCloud). \n Experience specifically building training and evaluation platforms for Large Language Models, Generative AI architectures, or Reinforcement Learning (RL) pipelines.\n Experience profiling ","salary_min":220000,"salary_max":292000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["computer-vision","mlops","llm","cloud","distributed-systems","robotics","data-pipeline","gpu"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5212860007?gh_jid=5212860007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T16:14:11Z","expires_at":"2026-09-29T13:37:28.517737Z","created_at":"2026-08-25T18:28:19.592013Z","updated_at":"2026-08-30T13:37:28.652109Z","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/e162808c-df72-4c08-9993-0438f336d9ac"},{"id":"e7e0e242-22d2-423a-88a2-fe5d88e92962","company_id":"30ae23c9-d589-41d4-be9b-1ff0a3d094bb","title":"Lab Automation - Robotics Engineer","slug":"lab-automation-robotics-engineer-e0fde2b2","description":"About Xaira Therapeutics \n Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London.\n About the Role \n We are building a next-generation lab automation and robotics platform to transform how biological experiments are executed, monitored, and scaled. This platform will bring together robotic arms, mobile platforms, lab instruments, sensors, computer vision, workflow orchestration, and AI-enabled autonomy to increase the speed, reliability, reproducibility, and scale of experimental biology.\n As a Robotics Engineer, Lab Automation, you will help turn real scientific workflows into robust automated systems. You will work closely with biologists, chemists, automation engineers, software engineers, and robotics experts to understand manual laboratory processes and translate them into reliable robotic execution.\n This is a hands-on engineering role for someone who enjoys building, integrating, testing, and debugging physical systems. You will contribute to robotic manipulation, instrument integration, perception, task execution, simulation, and multi-station lab automation workflows. You will also have opportunities to grow into more advanced robotics, autonomy, and AI-enabled laboratory automation over time.\n What You’ll Do \n \n Build, integrate, and maintain robotics software for robotic arms, mobile robots, sensors, grippers, and laboratory automation devices.\n Develop motion planning, manipulation, perception, and safety logic for robotic systems operating in real laboratory environments.\n Integrate laboratory instruments and devices through APIs, IoT interfaces, schedulers, and custom control software.\n Help build task execution frameworks using state machines, behavior trees, planners, and recovery logic for autonomous or semi-autonomous lab workflows.\n Benchmark and integrate computer vision methods for object detection, segmentation, tracking, pose estimation, localization, and scene understanding.\n Create and use simulation or digital twin environments for motion validation, workflow testing, synthetic data generation, and system debugging.\n Collaborate with scientists to translate biological and chemical workflows into automated protocols.\n Support multi-station system integration, automated material handling, sample tracking, validation, logging, and error recovery.\n Work hands-on with physical hardware to debug real systems, improve reliability, and iterate quickly.\n Evaluate modern AI, autonomy, foundation-model, reinforcement-learning, or imitation-learning approaches where they can improve real robotic lab execution.\n \n Qualifications (Required): \n \n Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or related field. \n Recent graduates with strong robotics, automation, hardware/software integration, or relevant project experience are encouraged to apply.\n PhD candidates are welcome to apply, particularly if they are excited by hands-on robotic system building, integration, and lab automation.\n Strong software engineering skills in one or more modern programming languages (e.g., Python, C++, C#), cloud-based workflows, and production software systems.\n Familiarity with robotics software frameworks such as ROS2, MoveIt, or comparable tools.\n Familiarity with computer vision, perception, motion planning, robotic manipulation, or sensor integration.\n Comfort working with physical hardware, debugging real systems, and learning by doing.\n Strong problem-solving skills, attention to detail, and ability to work across disciplines.\n Ability to communicate clearly with scientists, automation engineers, software engineers, and robotics experts.\n \n Preferred Qualifications: \n \n Experience with 6-axis robotic arms, autonomous mobile robots, grippers, machine vision systems, or automated material handling.\n Experience with OpenCV, object detection, segmentation, tracking, pose estimation, SLAM, localization, or scene understanding.\n Experience with Foxglove, Isaac Sim, MuJoCo, Gazebo, or other robotics simulation and debugging tools.\n Experience integrating laboratory instruments such as liquid handlers, plate hotels, incubators, readers, and microscopes.\n Experience with agentic AI frameworks (LangGraph, OpenAI Agents SDK, AutoGen, PydanticAI), Model Context Protocol (MCP), or AI systems that integrate language models with external tools and software.\n Familiarity wi","salary_min":150000,"salary_max":180000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["reinforcement-learning","gpu","generative-ai","robotics","computer-vision","agents"],"apply_url":"https://job-boards.greenhouse.io/xairatherapeutics/jobs/5212689007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-18T20:20:49Z","expires_at":"2026-09-29T13:51:03.109807Z","created_at":"2026-08-25T19:52:46.816947Z","updated_at":"2026-08-30T13:51:03.241025Z","company_name":"Xaira Therapeutics","company_slug":"xaira-therapeutics","company_logo_url":"https://www.google.com/s2/favicons?domain=xaira.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e7e0e242-22d2-423a-88a2-fe5d88e92962"},{"id":"0411758c-509d-41e4-8d8d-aa81039f05e7","company_id":"75dcf7c0-5121-45f1-8d1b-6bfbfe15072f","title":"Helix AI Engineer, Training Performance","slug":"helix-ai-engineer-training-performance-6acc6517","description":"Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA.\n \n Figure's vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced AI Training Performance Engineer to take our model training to the next level. This role is focused on improving distributed training frameworks for large scale model training, optimizing GPU kernels, exploring the relative gains of different accelerator types and co-designing our models to maximize utilization of our hardware.\n Responsibilities \n \n Optimize training performance for a 100B+ parameter models across 100k+ GPUs.\n Collaborate with the broader team on accelerator choice, cluster topology, scheduling, and hardware procurement decisions to inform future scaling.\n Write and optimize custom kernels (Triton/CUDA)\n Build tooling and dashboards for continuous performance monitoring, regression detection, and root-cause analysis across training jobs\n Optimize data loading and preprocessing pipelines so I/O never gates the accelerators\n Improve checkpointing, fault tolerance, and elastic restart so large jobs recover quickly from node failures without losing significant wall-clock time\n Partner with researchers to co-design model architectures and training recipes that are performant at scale (e.g., activation checkpointing strategies, mixed precision, sequence packing)\n Extend and contribute to kernel compilers (e.g., Triton, Gluon) to improve iteration speed and enable targeting of custom/non-NVIDIA accelerators\n Build and extend agentic systems that automatically generate, benchmark, and iterate on custom kernels\n Evaluate emerging accelerator architectures (AMD, TPU, SRAM-based ASICs, and other novel hardware) for fit with our training workloads, and lead proof-of-concept ports/benchmarks\n Explore different model/data parallelisms (FSDP, context parallel, expert parallel, etc.) to determine optimal configuration per model size.\n \n Requirements \n \n Bachelor's or Master's degree in Computer Science, Computer/Electrical Engineering, or a related field\n 3+ years in AI performance engineering, with significant time leading large-scale performance improvement projects\n Deep understanding of GPU architecture and performance characteristics (memory bandwidth, compute-bound vs. memory-bound ops, occupancy)\n Proficiency with profiling tools (Nsight Systems/Compute, PyTorch Profiler, HTA, or similar) and ability to translate traces into concrete optimizations\n Solid grasp of collective communication (NCCL) and modern networking concepts (RDMA, NVLink, InfiniBand/RoCE, topology-aware placement).\n Strong Python and CUDA/C++ skills; comfortable reading and modifying framework internals\n Experience debugging performance regressions and instability at scale (stragglers, hangs, OOMs, numerical divergence)\n Experience defining and reasoning about hardware-efficiency metrics (MFU/HFU) and using them to drive optimization priorities\n \n Bonus Qualifications \n \n Experience with heterogeneous or multi-datacenter training setups and cross-cluster orchestration\n Contributions to open-source ML systems projects (PyTorch, Megatron-LM, vLLM, DeepSpeed, JAX, etc.)\n Exposure to non-NVIDIA accelerators (AMD GPUs, TPU/Trainium/Inferentia, or custom silicon) and heterogeneous fleet management.\n \n \n The US base salary range for this full-time position is between $200,000 - $400,000 annually.\n The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.","salary_min":200000,"salary_max":400000,"location":"San Jose, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","pytorch","robotics","distributed-systems","gpu","agents"],"apply_url":"https://job-boards.greenhouse.io/figureai/jobs/4705296006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-14T04:53:35Z","expires_at":"2026-09-29T13:36:23.554918Z","created_at":"2026-08-25T18:27:56.071746Z","updated_at":"2026-08-30T13:36:23.689761Z","company_name":"Figure AI","company_slug":"figure-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=figure.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0411758c-509d-41e4-8d8d-aa81039f05e7"},{"id":"48b0c99b-9952-40ef-a088-d36c43da6f1d","company_id":"31ae48bc-c938-4c26-a348-0bf3c089a446","title":"Senior Software Engineer - AI Infrastructure Performance Insights \u0026 Observability","slug":"senior-software-engineer-ai-infrastructure-performance-insights-observability-bb558088","description":"CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at  www.coreweave.com . \n About this role \n We're looking for a Senior Engineer to be a driving force on CoreWeave's Benchmarking \u0026 Performance team, with a focus on building the performance insights and observability systems that make our AI infrastructure legible at every layer, from individual GPUs and NVLink/InfiniBand fabrics up through distributed training and inference workloads. You will own how we detect, diagnose, and surface performance signals across every data center in our global infrastructure, turning billions of raw telemetry events into real-time insight that engineers, product teams, and executives can act on with confidence.\n This is not a straightforward data engineering or BI role. The role will focus on building the observability and insight tooling that lets us answer, in near real time, whether a GPU fleet, a fabric, or a training run is performing the way it should, and why it isn't when it's not. If you're energized by building the systems that turn raw infrastructure telemetry into trusted, actionable performance intelligence, and you want that work to sit closer to the hardware and the workload than to a dashboard, this role was built for you.\n What you'll do \n \n Performance Insights \u0026 Observability - Design and build the systems that continuously assess AI infrastructure health and performance: GPU utilization and efficiency, interconnect (NVLink, InfiniBand, RoCE) fabric behavior, distributed training and inference throughput, and hardware degradation signals. Build the detection and diagnosis logic that surfaces anomalies and regressions before they become incidents, not just dashboards that report on them after the fact.\n Time-Series \u0026 Metrics Infrastructure - Own and extend our time-series database (TSDB) layer as the backbone of real-time observability. Write and optimize PromQL/MetricsQL queries that power alerting, anomaly detection, and trend analysis across thousands of GPUs and hundreds of benchmark runs. Bridge streaming metrics and batch-analytical workloads so engineers get sub-second answers during live incidents and analysts get complete historical context for root cause work.\n Fabric \u0026 GPU Telemetry - Build and validate the pipelines and metrics that make network fabric and GPU-level behavior observable and comparable across racks, clusters, and hardware generations, including gray failure detection, congestion and error-rate signals, and health scoring that holds up under audit.\n Data Lake Architecture (in support of insight work) - Design and build the performance data lake that underpins the above: table formats (Apache Iceberg, Parquet, Avro), hot/cold tiering, and schema evolution for latency distributions, throughput metrics, GPU utilization, cost-per-token, and hardware health signals. This is foundational infrastructure, not the end product.\n Query Optimization \u0026 Performance - Profile and tune query engines against columnar and time-series stores so that the observability layer meets its own strict P99 latency and freshness SLAs. Benchmark the benchmarking infrastructure itself.\n BI \u0026 Reporting (secondary) - Where needed, build self-service views (Grafana, Looker, or similar) for engineers, product managers, and executives, but as a downstream output of the insight and observability work above, not the primary deliverable.\n \n Who you are \n \n 5+ years of experience building distributed systems, observability platforms, or performance engineering tooling, ideally for infrastructure or ML systems rather than general-purpose BI.\n Strong coding in Python or Go (C++ a plus) and deep familiarity with networked systems, GPU infrastructure, and performance analysis.\n Hands-on experience with Kubernetes at production scale, CI/CD, and observability stacks (Prometheus, Grafana, OpenTelemetry) used to monitor and diagnose infrastructure, not just report on it.\n Working knowledge of time-series databases and fluency in PromQL or MetricsQL for building real-time alerting and anomaly detection, not only historical dashboards.\n Familiarity with data lake architectures and modern table formats (Iceberg, Parquet, Avro) sufficient to support an insights platform, though this is not the primary skill this role is hiring for.\n Comfortable working close to hardware and workload behavior: GPU utilization patterns, interconnect fabric health, distributed training/inference performance characteristics.\n Strong communicator comfortable collaborating with cross-functional teams ","salary_min":182000,"salary_max":242000,"location":"Sunnyvale, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","pytorch","llm","gpu","distributed-systems","infrastructure"],"apply_url":"https://coreweave.com/careers/job?4702966006\u0026board=coreweave\u0026gh_jid=4702966006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-13T20:47:10Z","expires_at":"2026-09-29T13:35:28.469364Z","created_at":"2026-08-25T18:27:34.745Z","updated_at":"2026-08-30T13:35:28.610554Z","company_name":"CoreWeave","company_slug":"coreweave","company_logo_url":"https://www.google.com/s2/favicons?domain=coreweave.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/48b0c99b-9952-40ef-a088-d36c43da6f1d"},{"id":"eaf53091-fb47-41f8-8b35-264e2d3c214d","company_id":"7f070aa1-7d20-4bbe-b6d2-68769923074e","title":"Senior Staff Software Engineer, DC Infrastructure","slug":"senior-staff-software-engineer-dc-infrastructure-b14db8aa","description":"Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.\n\n\n\nWe're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.\n\n\n\nWe're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.\n\n\n\nIf you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.\n\n\n\nCrusoe’s Data Center Infrastructure Engineering (DCIE) team is fundamental to our mission of providing AI hardware and infrastructure as a service. The team provides infrastructure for Crusoe’s fleet GPU’s and data center. The team sits at the nexus of high performance computing and AI infrastructure as a service.\n\nThe DCIE team owns, deployment maintenance, observability, critical environment, and automation. The team builds, and maintains GPU clusters, develops automation for logical and physical maintenance, provision systems, and observability tooling.\n\n\n\n\nABOUT THE ROLE:\n\nWe are seeking a highly skilled and motivated Software Engineer to join Crusoe’s Data Center Infrastructure Engineering team. This position is focused on the development of software for the management of a fleet of GPU servers as well as the data centers that house those systems. The role focuses on the developing and implementing  advanced diagnostic, observability, automation and repair tooling for high-performance GPU compute clusters.\n\nThe ideal new team member will be a hands-on problem solver who is comfortable working independently. The new team member will play a critical role in maintaining the health and scalability of Crusoe’s rapidly growing GPU fleet.\n\n\n\n\nWHAT YOU’LL BE DOING:\n\n - Developing and implementing deep-level diagnostics and troubleshooting of hardware faults within GPU racks and high-density compute systems.\n\n - Developing troubleshooting and automation tooling for GPU platforms including NVIDIA A100, H200, GB200, B200 and AMD 350X / 355X.\n\n - Developing automation and AI agents for executing component-level diagnosis and remediation for failed or degraded hardware.\n\n - In conjunction with data center operations develop innovative tooling and AI agents for managing the critical environment.\n\n - Developing tooling for post-repair validation and testing tools such as burn-in, Pytorch, and NVIDIA NCCL to ensure system stability and performance.\n\n - Own the deployment, monitoring, and operational support of developed tooling, ensuring solutions maximize GPU fleet availability and performance to drive customer success.\n\n - Developing automation and operational tooling for facilities management power as well as direct liquid cooling hardware systems\n\n\n\n\nWHAT YOU’LL BRING TO THE TEAM:\n\n - Software engineering experience.\n\n - The ability to identify a problem, rapidly develop a scalable solution and ship it.\n\n - Ability to lean in and assist team members working on critical or complex technical initiatives.\n\n - Ability to set the technical direction for a specific project and execute.\n\n - Expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, GCP etc.)\n\n - Strength in at least one programming language - Go, Python, Java, Rust.\n\n - Strong analytical and problem-solving skills.\n\n - Excellent communication and collaboration skills.\n\n - Ability to work independently and within a team\n\n\n\n\nNICE TO HAVE:\n\n - Experience with Temporal and Kubernetes.\n\n - Experience working directly with hardware vendors.\n\n - Background in large-scale GPU fleet operations or hyperscale data center environments.\n\n\n\n\nBENEFITS:\n\n - Industry competitive pay\n\n - Restricted Stock Units in a fast growing, well-funded technology company\n\n - Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents\n\n - Employer contributions to HSA accounts\n\n - Paid Parental Leave\n\n - Paid life insurance, short-term and long-term disability\n\n - Teladoc\n\n - 401(k) with a 100% match up to 4% of salary\n\n - Generous paid time off and holiday schedule\n\n - Cell phone reimbursement\n\n - Tuition reimbursement\n\n - Subscription to the Calm app\n\n - MetLife Legal\n\n - Company paid commuter benefit; $300 per month\n\n\n\nCompe","salary_min":250000,"salary_max":300000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","cloud","data-pipeline","pytorch","gpu","agents","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/crusoe/d0e72f9f-37af-4391-98cd-4e187cd224ae/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T22:51:19.788Z","expires_at":"2026-09-29T13:35:58.784823Z","created_at":"2026-08-25T18:27:46.34593Z","updated_at":"2026-08-30T13:35:58.918777Z","company_name":"Crusoe","company_slug":"crusoe","company_logo_url":"https://www.google.com/s2/favicons?domain=crusoe.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/eaf53091-fb47-41f8-8b35-264e2d3c214d"},{"id":"7f77c174-e767-4430-a27f-1c0da9eace2a","company_id":"7f070aa1-7d20-4bbe-b6d2-68769923074e","title":"Staff Software Engineer, DC Infrastructure","slug":"staff-software-engineer-7663b768","description":"Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.\n\n\n\nWe're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.\n\n\n\nWe're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.\n\n\n\nIf you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.\n\n\n\nCrusoe’s Data Center Infrastructure Engineering (DCIE) team is fundamental to our mission of providing AI hardware and infrastructure as a service. The team provides infrastructure for Crusoe’s fleet GPU’s and data center. The team sits at the nexus of high performance computing and AI infrastructure as a service.\n\nThe DCIE team owns, deployment maintenance, observability, critical environment, and automation. The team builds, and maintains GPU clusters, develops automation for logical and physical maintenance, provision systems, and observability tooling.\n\n\n\n\nABOUT THE ROLE:\n\nWe are seeking a highly skilled and motivated Software Engineer to join Crusoe’s Data Center Infrastructure Engineering team. This position is focused on the development of software for the management of a fleet of GPU servers as well as the data centers that house those systems. The role focuses on the developing and implementing  advanced diagnostic, observability, automation and repair tooling for high-performance GPU compute clusters.\n\nThe ideal new team member will be a hands-on problem solver who is comfortable working independently. The new team member will play a critical role in maintaining the health and scalability of Crusoe’s rapidly growing GPU fleet.\n\n\n\n\nWHAT YOU’LL BE DOING:\n\n - Developing and implementing deep-level diagnostics and troubleshooting of hardware faults within GPU racks and high-density compute systems.\n\n - Developing troubleshooting and automation tooling for GPU platforms including NVIDIA A100, H200, GB200, B200 and AMD 350X / 355X.\n\n - Developing automation and AI agents for executing component-level diagnosis and remediation for failed or degraded hardware.\n\n - In conjunction with data center operations develop innovative tooling and AI agents for managing the critical environment.\n\n - Developing tooling for post-repair validation and testing tools such as burn-in, Pytorch, and NVIDIA NCCL to ensure system stability and performance.\n\n - Own the deployment, monitoring, and operational support of developed tooling, ensuring solutions maximize GPU fleet availability and performance to drive customer success.\n\n - Developing automation and operational tooling for facilities management power as well as direct liquid cooling hardware systems\n\n\n\n\nWHAT YOU’LL BRING TO THE TEAM:\n\n - Software engineering experience.\n\n - The ability to identify a problem, rapidly develop a scalable solution and ship it.\n\n - Ability to lean in and assist team members working on critical or complex technical initiatives.\n\n - Ability to set the technical direction for a specific project and execute.\n\n - Expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, GCP etc.)\n\n - Strength in at least one programming language - Go, Python, Java, Rust.\n\n - Strong analytical and problem-solving skills.\n\n - Excellent communication and collaboration skills.\n\n - Ability to work independently and within a team\n\n\n\n\nNICE TO HAVE:\n\n - Experience with Temporal and Kubernetes.\n\n - Experience working directly with hardware vendors.\n\n - Background in large-scale GPU fleet operations or hyperscale data center environments.\n\n\n\n\nBENEFITS:\n\n - Industry competitive pay\n\n - Restricted Stock Units in a fast growing, well-funded technology company\n\n - Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents\n\n - Employer contributions to HSA accounts\n\n - Paid Parental Leave\n\n - Paid life insurance, short-term and long-term disability\n\n - Teladoc\n\n - 401(k) with a 100% match up to 4% of salary\n\n - Generous paid time off and holiday schedule\n\n - Cell phone reimbursement\n\n - Tuition reimbursement\n\n - Subscription to the Calm app\n\n - MetLife Legal\n\n - Company paid commuter benefit; $300 per month\n\n\n\nCompe","salary_min":215000,"salary_max":260000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","distributed-systems","data-pipeline","pytorch","gpu","cloud","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/crusoe/9469308d-d063-4449-bd53-3043836b1a0e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T22:50:13.339Z","expires_at":"2026-09-29T13:35:57.940694Z","created_at":"2026-04-13T09:41:26.548071Z","updated_at":"2026-08-30T13:35:58.079785Z","company_name":"Crusoe","company_slug":"crusoe","company_logo_url":"https://www.google.com/s2/favicons?domain=crusoe.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7f77c174-e767-4430-a27f-1c0da9eace2a"},{"id":"c329b188-7612-4641-ac6d-796f7502eb3d","company_id":"c587b06c-b6f0-4d1d-b694-6fb6abc2a6bb","title":"Senior Research Engineer, LLM Training \u0026 Post-Training","slug":"senior-research-engineer-llm-training-post-training-b05c8bf9","description":"Who We Are \n Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.\n Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.\n We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.\n The Way We Work\n The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice:\n \n Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping.\n Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through.\n Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together.\n Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work.\n Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most.\n Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact.\n \n  \n What We're Looking For\n We're are looking for an experienced Senior Research Engineer who has built, trained, and optimized modern transformer-based language models to join our Research Engineering function at Lightning.\n This role will focus on advancing how large language models are trained, fine-tuned, evaluated, and deployed across Lightning AI's platform and real-world customer workloads. It will work across model training, post-training, PyTorch, distributed systems, and AI systems engineering to improve model quality, training efficiency, and developer productivity while collaborating closely with researchers, infrastructure engineers, and customers.\n We're looking for someone who enjoys turning cutting-edge research into production systems. You have deep experience training and improving transformer-based language models, strong software engineering fundamentals, and a passion for solving difficult problems across model training, evaluation, and AI systems. Rather than building applications on top of existing models, you're motivated by improving the models themselves and the systems that power them. Our work spans models that power the Lightning AI platform, customer-specific model workloads, and research that translates into reusable training and platform capabilities.\n This role is hybrid with a minimum of 2 in-office days per week in San Francisco, Seattle, NYC, or London, with fully remote work considered for candidates outside of our office hub locations. All employees participate in occasional team and company offsites. \n  \n What You'll Do \n \n Design, build, and optimize training and post-training pipelines for large language models.\n Improve model quality through supervised fine-tuning, continued pretraining, preference optimization, reinforcement learning, evaluation, and experimentation.\n Build and improve PyTorch-based training infrastructure, tooling, and developer workflows.\n Optimize distributed training across multi-GPU environments by improving throughput, memory efficiency, scalability, and GPU utilization.\n Investigate model training issues, including convergence, instability, communication overhead, and performance bottlenecks.\n Design evaluation methodologies, benchmark models, analyze failure modes, and acheive model improvements through experimentation.\n Collaborate directly with customers to understand real-world workloads and translate those learnings into improvements across Lightning AI's research platform.\n Partner closely with research, infrastructure, and platform engineering teams to build production-ready AI systems.\n Contribute to open-source projects through new features, tooling improvements, documentation, and community engagement\n \n  \n What You’ll Need \n Required Qualifications \n \n Significant experience training, fine-tuning, evaluating, and/or optimizing transformer-based language models using PyTorch.\n Experience with modern LLM training and post-training techniques such as continued pretraining, SFT, RLHF, preference optimization (DPO, PPO, GRPO), reward modeling, or similar approaches.\n Strong understanding of distributed training and multi-node systems, ","salary_min":165000,"salary_max":310000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pre-training","search","fine-tuning","gpu","distributed-systems","llm","reinforcement-learning","pytorch"],"apply_url":"https://job-boards.greenhouse.io/lightningai/jobs/7860628003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T19:54:51Z","expires_at":"2026-09-29T13:33:58.434095Z","created_at":"2026-08-25T18:27:03.622997Z","updated_at":"2026-08-30T13:33:58.572247Z","company_name":"Lightning AI","company_slug":"lightning-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=lightning.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c329b188-7612-4641-ac6d-796f7502eb3d"},{"id":"105aa40e-13e5-4487-8a6c-c57474dfe43f","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Lead Software Architect, Rust","slug":"lead-software-architect-rust-a072e31f","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 At Anduril, our Battelspace Awareness Command and Control Software team specializes in solving complex, real-world problems through cutting-edge algorithms and intelligent software integrations. Operating in small, innovative teams, we push the boundaries of what's possible to deliver advanced technologies with mission-critical applications. Our commitment doesn't end with academic research or proof-of-concept experiments; we measure our success by the real-world impact of our deployed solutions. \n  \n ABOUT THE JOB \n We are looking for a Lead Software Architect to join our rapidly growing C2 Systems team in  Waltham, MA.   In this role, you will be responsible for defining the architectural direction of large-scale, real-time, mission-critical C2 software that powers Anduril's air and missile defense and battlespace awareness capabilities. You will lead the design of high-performance systems spanning tactical edge deployments to distributed backend infrastructure, make critical trade-offs between performance, modularity, and maintainability at scale, and mentor senior engineers across the C2 organization . This will require deep expertise in  modern C++ and Rust , experience architecting numerics-heavy real-time systems, fluency with asynchronous/multithreaded programming (e.g., Tokio), and a strong grasp of the complex intersection of software and math — including state estimation, target tracking, optimization, and dynamic programming (MCP / Bellman equations) . If you are someone who thrives on ambitious defense problems, enjoys troubleshooting real-world systems where issues could range from electromagnetics to faulty bit encodings to incorrect math assumptions, and wants to build software that is beyond a proof-of-concept — part of real tactical code deployed to the warfighter — then this role is for you\n WHAT YOU’LL DO\n \n Define and drive the architectural vision for large-scale C2 software systems that ingest, fuse, and act on data from diverse sensors in real time\n Lead the design and implementation of performant, real-time, numerics-heavy algorithms in Rust and/or C++ at production scale\n Partner closely with research scientists to transition advanced algorithms (target tracking, state estimation, sensor-effector pairing, asset scheduling) from prototype into tactical, deployed code\n Make high-leverage architectural trade-offs across performance, modularity, testability, and maintainability for mission-critical, edge-deployed systems\n Mentor and technically lead senior engineers, setting coding standards, review processes, and CI/CD best practices across the team\n Engage directly with customers (DoD agencies, Army, Air Force, MDA, SCO) to ensure successful outcomes for mission-critical needs\n Troubleshoot complex, real-world system issues spanning software, math assumptions, sensor behavior, and networking\n Contribute to all phases of the software development lifecycle including prototyping, modeling \u0026 simulation, field testing, and deployment\n Help shape hiring and technical growth of the broader C2 organization as it hyper scales\n \n REQUIRED QUALIFICATIONS\n \n 10+ years of software engineering experience with a Bachelor's degree (or equivalent) in Computer Science, Applied/Computational Mathematics, Electrical Engineering, Aerospace Engineering, Controls/Dynamical Systems, Statistics, or related field\n Expert-level proficiency in modern C++ and/or Rust, including asynchronous and multithreaded programming (e.g., Tokio for Rust)\n Proven experience architecting large-scale, production-grade codebases in real-time or high-performance environments\n Deep experience writing performant, real-time software with numerics-heavy algorithms\n Strong foundation in applied mathematics: probability theory, linear algebra, optimization, differential equations (ODEs), and statistics\n Experience with CI/CD, unit testing, git version control, and microservices\n Eligible to obtain and maintain an active U.S. Secret security clearance\n \n PREFERRED QUALIFICATIONS\n \n M.S. or Ph.D. in a technical field (dual academic background in software + math highly valued)\n Domain expertise in target tracking, state estimation, Kalman filters, sensor fusion, or signal processing \n Prior D","salary_min":253000,"salary_max":336000,"location":"Waltham, MA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["computer-vision","microservices","llm","cloud","payments","gpu","rust"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5210357007?gh_jid=5210357007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T15:06:35Z","expires_at":"2026-09-29T13:37:15.344951Z","created_at":"2026-08-25T18:28:18.938854Z","updated_at":"2026-08-30T13:37:15.481467Z","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/105aa40e-13e5-4487-8a6c-c57474dfe43f"},{"id":"9941177a-20bc-4609-805c-b67d8a59d3a8","company_id":"fb64b18b-041a-43de-886d-f506d1ab94a4","title":"Senior AI Platform Engineer, Infrastructure Services","slug":"senior-ai-platform-engineer-infrastructure-services-d9d4ca58","description":"Our Purpose \n At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.\n About Us \n SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.\n Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.\n What Are We Looking For? \n We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.\n As a Senior AI Platform Engineer, Infrastructure Services, you will be tasked with taking ownership of our AI Gateway infrastructure (built on Kong AI Gateway), the system that authenticates, routes, rate-limits, and monitors AI coding assistant traffic org-wide, while also being fluent enough across our broader platform stack to design solutions that span the two. This is a high-autonomy, high-scope role: you will set technical direction for AI infrastructure, drive incident response and reliability work, and partner closely with the engineers who own our CI/CD, GitOps, and artifact systems rather than working in isolation from them.\n What Will You Do?\n Primary responsibilities include:\n \n Work on the AI Gateway platform: architect, harden, and scale our Kong AI Gateway deployment (Konnect Hybrid on KCP/EKS), including auth (Okta/OIDC), consumer tiers and budgets, rate limiting, semantic caching, and observability.\n Lead reliability and incident response: drive root-cause analysis and remediation for gateway issues (timeouts, latency, capacity, failover) and build the monitoring/alerting needed to catch them before users do.\n Design across the platform, not just the gateway: work fluently with our CI/CD (Jenkins, JPAAS), GitOps and Kubernetes deployment tooling (ArgoCD across dev/gov/prod), artifact management (Artifactory/Xray), GitHub Enterprise administration, and GitHub Actions runner fleet, so that AI infrastructure decisions account for how the rest of the platform actually works.\n Evaluate and roll out AI developer tooling: run structured pilots and adoption efforts for tools like AI-assisted PR review (Qodo) and engineering metrics platforms (LinearB), and make clear build-vs-buy recommendations.\n Set technical direction and mentor: define architecture and standards for AI infrastructure, review designs across the team, and raise the bar for other engineers working in this space.\n Partner cross-functionally: work directly with security, DevEx, and product engineering teams consuming the gateway to translate their needs into platform capabilities.\n Host and serve local models: stand up and operate self-hosted/open-weight model serving infrastructure (e.g. vLLM, NVIDIA Triton/NIM, TGI, Ollama) for workloads where routing to an external provider isn't the right fit, including GPU capacity planning, autoscaling, and cost/performance tuning.\n Support the broader model lifecycle: help build LLMOps practices such as model versioning, evaluation, and safe rollout, plus supporting infrastructure for retrieval-augmented generation (vector stores, embedding pipelines) as use cases mature.\n Track usage and cost: build observability into token usage, latency, and spend across both API-based and self-hosted models so the business can see what AI infrastructure actually costs.\n \n What Skills and Knowledge Will You Bring?\n Ideal candidates will have:\n \n 5 or more years of experience in platform, infrastructure, or DevOps engineering, with a track record of owning systems end-to-end in production.\n Hands-on experience with API gateway technologies (Kong, Envoy, Apigee, or similar); direct experience with AI/LLM gateway patterns (rate limiting, semantic caching, prompt/response observability) is a strong plus.\n Strong Kubernetes and GitOps experience (ArgoCD or comparable), an","salary_min":132000,"salary_max":182000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["mlops","embeddings","api-design","code-generation","fine-tuning","llm","rag","gpu"],"apply_url":"https://www.sentinelone.com/jobs/?gh_jid=7823236003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-06T14:00:30Z","expires_at":"2026-09-29T13:49:23.67821Z","created_at":"2026-08-25T18:33:46.305318Z","updated_at":"2026-08-30T13:49:23.811061Z","company_name":"SentinelOne","company_slug":"sentinelone","company_logo_url":"https://www.google.com/s2/favicons?domain=sentinelone.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9941177a-20bc-4609-805c-b67d8a59d3a8"},{"id":"d24599a8-79cd-4451-bfb0-9da12e6ee90e","company_id":"7f070aa1-7d20-4bbe-b6d2-68769923074e","title":"Principal Systems Software Engineer","slug":"principal-systems-software-engineer-9b3eee44","description":"Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.\n\n\n\nWe're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.\n\n\n\nWe're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.\n\n\n\nIf you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.\n\n\n\n\nABOUT THIS ROLE:\n\nAs the Principal Systems Software Engineer, you will serve as the visionary lead for Crusoe’s next-generation AI infrastructure. This is a role for an industry-recognized expert who has already \"seen the movie\" at hyperscale and is ready to redefine the I/O path for the age of generative AI. You aren't just building a cloud; you are designing the fluid fabric that unifies Bare-Metal-as-a-Service (BMaaS), Intelligent IaaS, and Elastic CaaS into a single, high-performance pool of intelligence.\n\nIn this position, you will bridge the gap between silicon and software, advising executive leadership on critical hardware/software co-design pivots while remaining hands-on enough to lead elite R\u0026D teams in shipping production-grade kernel and orchestration code. We are looking for a master of the I/O path who can push massive-scale training workloads to the theoretical limits of hardware. This is a full-time position.\n\n \n\n\nWHAT YOU’LL BE WORKING ON:\n\n - Unifying Infrastructure Pillars:\n   \n   - Bare-Metal-as-a-Service (BMaaS): Architect systems that deliver raw GPU throughput via zero-latency InfiniBand/RDMA fabrics for massive-scale training.\n   \n   - Intelligent IaaS: Design highly optimized, thin virtualization layers using KVM or custom micro-VMs to provide enterprise-grade isolation without the \"virtualization tax.\"\n   \n   - Elastic CaaS: Build a high-performance container substrate (utilizing Kubernetes or Slurm) that allows AI workloads to burst and scale across heterogeneous GPU nodes.\n\n - Mastering the I/O Path: Lead the architectural design of our internal cloud fabric, drawing on experience from top-tier hyperscalers to drive the technical roadmap for SR-IOV, RDMA, and virtualized GPU scheduling.\n\n - Advanced R\u0026D Leadership: Lead elite workstreams to prototype and productionize novel methods for managing memory, networking, and compute that don't yet exist in standard cloud distributions.\n\n - Technical Strategy \u0026 Documentation: Draft white papers and RFCs that define the next two years of Crusoe’s compute and networking stack.\n\n - High-Level Debugging: Work alongside Staff and Senior engineers to resolve complex race conditions in the I/O path and optimize kernel-level memory pinning for GPU clusters.\n\n - Industry Influence: Represent Crusoe in open-source communities and industry forums to influence the global direction of cloud-native AI infrastructure.\n   \n    \n\n\nWHAT YOU’LL BRING TO THE TEAM:\n\n - Hyperscale Provenance: 12+ years of experience designing and shipping core infrastructure at a major hyperscaler (e.g., OCI, AWS, Azure, GCP) or a specialized HPC cloud.\n\n - Deep Systems Authority: Authoritative knowledge of the Linux kernel, virtualization internals (KVM, QEMU, Firecracker), and high-performance networking (RoCE v2, InfiniBand).\n\n - Hardware-Software Co-Design: Proven ability to design software that maximizes the performance of NVIDIA/AMD GPUs and high-speed NICs.\n\n - R\u0026D Leadership: Experience leading cross-functional teams through high-ambiguity projects and delivering production-ready, mission-critical systems.\n\n - Industry Contributions: A portfolio of significant contributions to the field, which may include patents, major open-source contributions, or published research in distributed systems.\n\n - Communication Mastery: The rare ability to explain the nuances of memory-mapped I/O to an engineer and the business value of a new fabric architecture to the Board.\n\n - Mandatory Education: A Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related analytical field (or equivalent professional experience).\n   \n    \n\n\nBONUS POINTS:\n\n - Patent Holder: Possession of patents related to network virtualization, GPU scheduling, or distributed file systems.\n\n - Open So","salary_min":260000,"salary_max":340000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["generative-ai","llm","distributed-systems","gpu"],"apply_url":"https://jobs.ashbyhq.com/crusoe/a1ad6adb-6706-4490-9512-fd8fcb51dae9/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T20:07:39.852Z","expires_at":"2026-09-29T13:35:58.694028Z","created_at":"2026-08-25T18:27:46.341205Z","updated_at":"2026-08-30T13:35:58.826687Z","company_name":"Crusoe","company_slug":"crusoe","company_logo_url":"https://www.google.com/s2/favicons?domain=crusoe.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d24599a8-79cd-4451-bfb0-9da12e6ee90e"},{"id":"de1ba9d8-dfc0-4bc4-ac95-9b2151e1c131","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior Software Engineering Manager, Simulation Platforms ","slug":"senior-software-engineering-manager-simulation-platforms-632061f4","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n About the Team   \n The Air Dominance \u0026 Strike team at Anduril develops aerial and multi-domain robotic systems. The team is responsible for taking products like Fury (unmanned fighter jet) and Barracuda (air-breathing cruise missile) from concept to product. The team also develops Lattice for Mission Autonomy, Anduril’s premier software platform that enables masses of Fury, Barracuda, and other first and third party robots to collaborate across various missions. We work in close coordination with specialist teams like Perception, Motion Planning, Hardware, and Test Engineering to solve some of the hardest problems facing our customers.   \n This team builds high-fidelity simulation platforms used to evaluate advanced aerospace and mission systems in realistic, contested environments. The team develops digital models and modern, parametric simulators that represent sophisticated adversary behaviors, providing rapid iteration cycles for testing and training.   \n The long-term focus is to modernize legacy, monolithic simulation frameworks, transitioning them toward modern, modular architectures with stable APIs, robust versioning, and automated testing. This work involves a mix of software, systems engineering, real-time simulation, and API design, with a direct impact on how next-generation defense platforms are evaluated.   \n Responsibilities   \n \n Grow, mentor, and scale the engineering team significantly, fostering a high-performance culture \n Partner closely with the Chief Engineer to define the technical direction, modernize simulation architectures into modular systems, and own successful project execution.\n Maintain and build strong relationships with key stakeholders across government-owned simulation environments and defense funding, acquisition, and innovation agencies. \n Partner with business development teams to identify new opportunities, evaluate technical feasibility, and lead the technical writing of proposals to expand the team's footprint.   \n \n Required Qualifications   \n \n Active U.S. Top Secret (TS) security clearance. \n 5+ years of experience managing software engineering teams, with a proven track record of hiring, scaling, and developing talent. \n 5+ years of hands-on software development experience with a strong understanding of complex systems architecture, API design, and modern software engineering practices. \n Experience developing, deploying, and testing software within secure, classified, or air-gapped environments. \n Experience partnering with business development teams, writing technical proposals, or helping scope engineering work for government contracts. \n Proven ability to manage customer expectations and negotiate technical delivery paths when stakeholders have competing priorities.   \n \n  \n Preferred Qualifications   \n \n Prior experience in modeling and simulation within the defense sector, particularly with federating multiple simulators together. \n Familiarity with translating intelligence assessments of adversary capabilities into high-fidelity modeled software environments. \n Familiarity with modern defense acquisition, test, and innovation organizations (such as AFLCMC, TRMC, or DIU). \n A desire to remain close to the technology, with the ability to participate in high-level system design reviews and evaluate architectural decisions.   \n US Salary 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. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the i","salary_min":220000,"salary_max":292000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["api-design","robotics","gpu","cloud","computer-vision","payments"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5171141007?gh_jid=5171141007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T16:16:13Z","expires_at":"2026-09-29T13:37:25.264055Z","created_at":"2026-08-25T18:28:19.434876Z","updated_at":"2026-08-30T13:37:25.395685Z","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/de1ba9d8-dfc0-4bc4-ac95-9b2151e1c131"},{"id":"ba51debf-3aee-45ee-840d-cc214a3e4e46","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Director / Senior Director, Research Engineering, Life Sciences AI","slug":"director-senior-director-research-engineering-life-sciences-ai-5baf53aa","description":"Your Impact at LILA \n LSAI (Life Sciences Artificial Intelligence) is building the computational platform that powers Lila's work in the life sciences. We are looking for a Research Engineer to own and build the core codebase that our models plug into, the foundation on which our scientists build and ship their work. This role is part of the LSAI leadership team and reports to the SVP of Generative Biology.\n This role combines deep hands-on IC work with growing management responsibility. You will personally architect and build the core platform while also building and leading a team as headcount grows. IC contribution remains the top priority for this role.\n What You'll Be Building \n \n Design, build, and own the foundation of the LSAI codebase, the core infrastructure that scientist-owned models plug into.\n Set and enforce engineering standards for code quality, testing, versioning, documentation, and repository structure.\n Make architectural decisions that balance rigor with the reality that most contributors are scientists first, engineers second.\n Anticipate infrastructure bottlenecks and define the platform roadmap to enable rapid iteration while maintaining quality and reproducibility.\n Build and manage an engineering team over time while remaining a primary hands-on contributor.\n \n What You'll Need to Succeed \n \n Strong track record designing and building core software platforms or frameworks that scientists and engineers depend on.\n Deep platform architecture expertise, with biological applications such as protein design, nucleic-acid design, or cell foundation models as a plus.\n Experience building infrastructure and tooling alongside scientists in a research environment without sacrificing velocity.\n Full ML lifecycle expertise across data, training, evaluation, and MLOps, with a track record of taking research code to production.\n Comfort shifting between hands-on building and strategic leadership without letting either crowd out the other.\n Experience mentoring people and setting technical practices across a team or organization, beyond individual output.\n \n Bonus Points For \n \n Experience in a bioML lab or scientific computing environment.\n Familiarity with or curiosity about computational biology, protein modeling, or ML-adjacent codebases.\n Comfort working around model builders, even if you do not build the models yourself.\n Performance engineering experience, including profiling and optimizing training and inference.\n Experience writing or tuning CUDA or Triton kernels.\n Ability to reason about GPU utilization, MFU/HFU, memory bandwidth, and kernel-level bottlenecks.\n Deep expertise in the modern ML systems stack, including PyTorch internals, mixed precision, and distributed training across multi-GPU or multi-node clusters.\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $320,000 — $490,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.\n We’re All In \n Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.\n Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy .\n A Note to Agencies \n Lila Sciences does not accept unsolicited resumes from an","salary_min":320000,"salary_max":490000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","mlops","generative-ai","distributed-systems","search","gpu","research"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4343454009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T16:12:25Z","expires_at":"2026-09-29T13:48:20.538266Z","created_at":"2026-08-25T18:33:16.840958Z","updated_at":"2026-08-30T13:48:20.674505Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ba51debf-3aee-45ee-840d-cc214a3e4e46"},{"id":"06ccd71c-7e21-4ecf-ba96-f0994ca19a7a","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Perception Engineer ","slug":"perception-engineer-584c9492","description":"Perception Engineer .   Ref. No.  N322 BOSTON – REMOTE U.S. ONLY FULL-TIME   \n   What You’ll Do:   \n \n Connect/drive project-level impact through technology solutions..    \n Design, develop, implement, and fix features in codebase.    \n Formulate problems, architect solutions, and design processes.    \n Train and deploy new AI models.    \n Analyze model performance and identify improvements.    \n Research/evaluate emerging technologies to enhance AI models.    \n Prototype, evaluate, implement, and iterate on solutions.   \n \n     What You Bring:   \n \n Requires Bachelor’s or higher in Computer Science, Electrical Engineering, Robotics, or or a closely related technical field    \n Two  years of industry experience in automotive industry software development.    \n Experience must include:   \n \n production-level software development,    \n model deployment,    \n integration and validation for robotics,    \n testing/debugging algorithms,    \n machine learning applications,    \n Python,    \n C++,    \n PyTorch,    \n GPU training,    \n acceleration and inference optimization,    \n TensorRT/CUDA,    \n CI/CD pipelines, and   \n Git.   \n \n \n Ref Job No. N 322   \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 $165,000 — $197,698 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 differently; it’s not only good for our business, it’s the right thing to do.  \n Scale up, not starting up. \n Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.\n Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit  www.Motional.com and follow us on Twitter , LinkedIn ,  Instagram and YouTube .\n Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.","salary_min":165000,"salary_max":197698,"location":"Boston, MA","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["mlops","robotics","pytorch","gpu","autonomous-vehicles"],"apply_url":"https://motional.com/open-positions/?gh_jid=7826405003#/7826405003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-04T19:06:35Z","expires_at":"2026-09-29T13:36:27.395146Z","created_at":"2026-08-25T18:27:56.98604Z","updated_at":"2026-08-30T13:36:27.529521Z","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/06ccd71c-7e21-4ecf-ba96-f0994ca19a7a"}],"page":1,"per_page":20,"total":527,"total_is_exact":true,"total_pages":27}