Director, Engineering

• AutonomyAs the Director of Engineering

• Autonomy, you will provide the strategic leadership and executive vision for the teams responsible for major components of the core autonomy system and its safety architectures.

You will build and scale a world-class organization dedicated to advancing Physical AI, focusing on edge-deployed machine learning, deterministic safety fallbacks, and real-time execution. Rather than building a traditional closed ecosystem, your teams will develop the robust onboard intelligence and safety guards required to safely evaluate next-generation models, benchmark autonomous capabilities, and collect high-value, long-tail data in complex real-world environments. Operating at the intersection of advanced research and rigorous systems engineering, you will hold ultimate accountability for ensuring that these core system components maneuver safely, predictably, and intelligently on physical hardware.

Executive Leadership & Strategy: Define the technical vision and organizational roadmap for major components of the core autonomy system.

You will align complex technical goals with Uber's overarching mission to accelerate the broader autonomous ecosystem

Core AI & Safety Architecture: Direct the development of robust edge software, guiding the integration of advanced ML models with deterministic, rule-based safety fallbacks. Ensure the system exhibits strictly compliant, collision-free operations while adhering to rigorous real-time compute and kinematic constraints on the vehicle

Research & Evaluation Focus: Champion the transition of cutting-edge AI into production-ready software designed specifically to safely orchestrate vehicle operations for advanced research, ecosystem benchmarking, and scaled data collection mission

Organizational Growth: Build, manage, and mentor a high-performing organization of engineering managers, principal engineers, and technical leaders, fostering a culture of rigorous execution and safety-first engineering

Cross-Functional Execution: Partner directly with other AV departments to ensure a seamless transition from virtual testing to physical fleet deployment. You are the definitive owner of your core system components' real-world safety metrics and deployment readiness

What You'll Need

12

• years of professional experience in Software Engineering, Machine Learning, or Autonomous Systems

5

• years of leadership experience managing and scaling engineering organizations, including experience managing other managers and senior technical leaders (Principals/Staff)

Proven track record of successfully deploying complex, real-time software systems to physical hardware (edge compute, robotics, or autonomous vehicles)

Bachelor's degree in Computer Science, Computer Engineering, or a related technical field

Bonus Points If

Advanced degree (MS/PhD) in Computer Science, Robotics, or a related technical field.

Deep understanding of high-performance system optimization for edge devices (C

•

• , CUDA, Linux, RTOS)

Extensive experience architecting autonomous safety systems, fallback logic, and real-time control constraints

Familiarity with modern AI/ML frameworks (e.g., PyTorch) and the challenges of running deep learning models on constrained in-vehicle compute

Strong background working with ecosystem partners, third-party technology evaluation, or reference architectures

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 raceand Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.