Principal Engineer - Evaluation & Simulation

Uber Uber · Consumer · San Francisco, CA +1 · Engineering

This role focuses on building and scaling large-scale simulation platforms for autonomous vehicle (AV) testing and validation. It involves designing high-fidelity simulation frameworks, integrating sensor data and behavioral models, defining evaluation metrics, and generating edge-case scenarios. The goal is to accelerate AI research and ensure safety benchmarking for AVs.

What you'd actually do

  1. Lead the technical roadmap for our large-scale, cloud-based simulation platform, ensuring it can efficiently scale to run millions of closed-loop scenarios and validate complex urban edge cases
  2. Design and oversee the implementation of advanced simulation frameworks that integrate sensor data (LiDAR, camera, radar), cutting-edge neural rendering, and highly realistic traffic agent behaviors
  3. Define the deterministic and probabilistic evaluation metrics used to score autonomous behavior. Pioneer the systems used for procedural and data-driven generation of rare, long-tail edge-case scenarios
  4. Act as the crucial bridge between simulation infrastructure and the core ML stack, ensuring seamless integration so that onboard models can be trained, tested, and validated in highly accurate virtual environments prior to field deployment
  5. Mentor senior and lead engineers, fostering a culture of rigorous software architecture, testing, and engineering excellence. You will influence the technical direction of multiple infrastructure and autonomy teams

Skills

Required

  • 10+ years of working experience in Software Engineering, Autonomous Systems, Simulation, or Robotics
  • Proven experience leading the architecture and delivery of large-scale distributed systems or complex simulation platforms from conception to production
  • Bachelor's degree in Computer Science, Computer Engineering, or related fields
  • Expert-level proficiency in C++ and Python within Linux environments
  • Deep expertise in high-performance computing, system optimization, and cloud architecture (AWS, GCP, etc.)

Nice to have

  • Advanced degree (MS/PhD) in Computer Science, Robotics, or a related technical field
  • Extensive experience building AV simulation platforms, rendering engines, or complex video game engines (e.g., Unreal Engine, Unity, custom C++ engines)
  • Deep understanding of sensor modeling (Camera, LiDAR, Radar) and vehicle kinematics
  • Recognized expertise in the field (e.g., relevant patents, open-source contributions, or publications)

What the JD emphasized

  • rigorously evaluate
  • evaluation infrastructure
  • safety benchmarking
  • large-scale
  • complex urban edge cases
  • rare, long-tail edge-case scenarios
  • highly accurate virtual environments

Other signals

  • large-scale virtual testing
  • rigorously evaluate state-of-the-art autonomous capabilities
  • accelerates AI research
  • safety benchmarking