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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 will be 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 (millions of Uber trips every hour across cities, conditions, and edge cases create the data autonomy has been missing). We will build platforms that harness scale and real-world complexity to reimagine how the world moves. We are seeking a Sr. Staff Hardware Engineer to serve as the overarching architect for our entire sensing and compute platform. In this role, you will look across the entire vehicle platform definition & topology, balancing the trade-offs between sensor fidelity, compute throughput, thermal constraints, and power delivery.
Job Responsibility:
System Architecture & Topology: Participate in designing the L4 hardware architecture, determining the optimal sensor placement (FoV coverage vs. vehicle aerodynamics), sensor mix (redundancy vs. cost), and compute topology (centralized vs. zonal) to meet safety and data collection goals
Supplier Engagement: Participate in the technical roadmap relationships with key industry partners
Multi-Modal Integration: Solve complex system-level challenges such as multi-sensor time synchronization, electromagnetic interference mitigation between high-power compute and sensitive RF sensors, and centralized thermal management strategies
Requirements:
Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, or related field
Strong background in complex hardware system architecture, with 3+ years of experience building Autonomous Vehicles, Robotics, or Aerospace products
Understanding of overall AV sensing modalities and their underlying physics, data structures, and failure modes
Understanding of high-performance compute systems and high-speed data interconnects in constrained environments
Nice to have:
Experience with a L4 autonomous vehicle platform or a complex ADAS system
Knowledge of Functional Safety and how hardware architecture supports system-level safety goals
Familiarity with NVIDIA Drive platforms (Orin/Thor) and their hardware integration guidelines
Experience with vehicle homologation requirements and environmental qualification standards
What we offer:
Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan