Staff System Engineer - AV Labs

About the role and team Uber 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. What you'll do Autonomous Vehicle Evaluation : Lead the technical assessment and capability benchmarking of autonomous systems of our partners. Audit partner performance against Uber AV Labs' safety and efficiency KPIs to validate technology readiness. System Integration Validation : Define and execute the integration strategy for hardware and software. Develop rigorous validation plans to ensure stacks meet interface, throughput, and performance requirements within our data collection fleet. Performance Benchmarking : Develop multi-modal metrics (road vs. simulation) to independently benchmark system performance against human capabilities and internal standards. Safety & Compliance Standards : Build safety cases and hazard analyses. Work with different teams to ensure that our partners' fault management logic and minimum risk maneuvers align with our internal safety standards and risk tolerance. Technical Liaison & Roadmap Alignment : Act as the primary technical point of contact between our internal engineering teams and external engineering organizations. Manage technical gating criteria for releases and track issues to resolution to ensure continuous development. Basic Qualifications 6+ years of working experience in the Robotics or Autonomous Systems industry. Strong system thinking skills with the ability to decompose complex driving capability challenges to practical, scalable solutions. Bachelor's or Master's degree in Computer Science, Transportation Engineering, Statistics, Computer Engineering, Electrical Engineering or related fields. Proficiency in Python and Linux environments. Preferred Qualifications Professional experience in safety critical autonomous systems or PhD research experience in traffic safety. Proven track record of defining release processes and safety criteria for real-world autonomous systems. Hands-on experience with system validation tools with development skills on simulation and data mining. Background in functional safety, SOTIF, Cybersecurity for automotive development. For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. You 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. Ready to Ride? This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you. You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. Equal Employment Opportunity Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form: #J-18808-Ljbffr Uber