{"id":1269099,"url":"https://alion.io/job/uber-staff-software-engineer-ml-av-labs","title":"Staff Software Engineer - ML AV Labs","company":{"id":230,"name":"Uber","domain":"uber.com","url":"https://alion.io/company/uber","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":93,"open_postings":110,"ghost_share":0,"stale_share":0.464,"repost_share":0.009,"time_to_fill_p50_days":5,"computed_at":"2026-10-02T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":232000,"max":258000,"currency":"USD","period":"year","gross":null,"usd_annual":258000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"C++","optional":true},{"name":"Computer Vision","optional":true},{"name":"CUDA","optional":true},{"name":"CUDA Toolkit","optional":true},{"name":"ROS","optional":true}],"status":"live","first_seen_at":"2026-09-25T21:46:52Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-10-02T23:15:07Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"About the Role\nUber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team is focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race-and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.\nAs a Staff ML Engineer, you will be at the forefront of Physical AI, building advanced autonomy algorithms and models to add rich semantics to our massive driving data. You will set the technical direction for the development and implementation of machine learning techniques that enables better data mining, deep scene understanding, and causal modeling of ego vehicle behavior. You aren't just solving known problems; you are identifying the next generation of challenges in AV, designing the architectural foundations to solve them, and raising the bar for technical excellence across the entire engineering organization.\nWhat the Candidate Will Do\nSet the technical roadmap and lead the delivery of state-of-the-art Machine Learning systems:\nAlgorithm Development: Lead the strategy for development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake.\nArchitecture & System Design: Design and oversee the implementation of complex, large-scale ML systems, ensuring seamless integration between upstream sensor data.\nTechnical Mentorship & Influence: Mentor senior and lead engineers, fostering a culture of rigorous experimentation and engineering excellence. You will influence the technical direction of multiple teams.\nPlatform Evolution: Define the requirements for high-quality datasets and auto-labeling systems, ensuring our ML infrastructure evolves at the speed of the latest research.\nCross-Organizational Leadership: Act as a bridge between AV Labs and other Uber engineering units to ensure that autonomous technology is successfully integrated and deployed at scale.\nBasic Qualifications\n8+ years of working experience in the ML, Robotics, or Autonomous Systems industry.\nProven experience leading large-scale technical projects from conception to production.\nBachelor’s degree in Computer Science, Computer Engineering, or related fields.\nExpert-level proficiency in Python and Linux environments.\nDeep expertise in modern AI/ML frameworks (e.g., PyTorch).\nPreferred Qualifications\nPhD degree in Computer Vision, Robotics, or Machine Learning with a focus on Autonomous Driving.\nExtensive experience with C++, CUDA, and high-performance system optimization.\nDeep understanding of the Robot Operating System (ROS) or similar autonomous middleware.\nRecognized expertise in the field (e.g., publications in CVPR, NeurIPS, ICRA or patents related to AV).\nExperience building and scaling \"Foundation Models\" for physical world interaction.\n For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.\nYou will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.","description_format":"text","description_chars":3396,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Transportation & Logistics","Ride Hailing"],"lifecycle":[{"event":"open","at":"2026-09-25T23:26:44Z"}],"liveness":{"score":37,"band":"fade","label":"Fading","p_open":1,"p_active":0.666,"p_room":0.55,"age_days":6,"expected_fill_days":5,"reasons":["conf:10","velocity","win:tail","comp:brand"],"computed_at":"2026-10-02T05:45:00Z"},"pay":{"stated_usd_annual":258000,"is_top_pay":false},"html_url":"https://alion.io/job/uber-staff-software-engineer-ml-av-labs","json_url":"https://alion.io/job/uber-staff-software-engineer-ml-av-labs.json","meta":{"generated_at":"2026-10-03T03:14:54Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2936,"day_limit":5000,"remaining_today":2064,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}