We’re reinventing personal transportation—making the future safer, cleaner, and more enjoyable. We’ve created our vehicle specifically for dense, complicated urban environments. Zoox is the only driving vehicle on the market with bidirectional driving capabilities and four-wheel steering, allowing us to maneuver through compact spaces and change directions without the need to reverse. The future is for riders!
Our growing Perception team is searching for an Engineering Manager for the Perception Occupancy and Rare Events team. Our perception stack is responsible for building Zoox’s world-class 3D environment model from multi-modal sensor data. We create novel AI architectures that combine the latest academic results with many in-house innovations in creative ways. Our algorithms are relentlessly optimized and tuned to run efficiently and effectively on a wide variety of real-life data as well as in simulation.
You will be responsible for leading high-impact Perception teams with their technical roadmap and milestone goals. You will be closely collaborating with other AI teams including Simulation, Sensor and Hardware, and Systems Design and Mission Assurance teams to deliver an exceptional objects occupancy perception system encompassing modalities such as vision, lidar, radar and long-wave IR. You will lead a diverse, experienced team with a rapidly growing scope and responsibility while also working on some of the most complex problems in artificial intelligence, perception, and sensor fusion.
In this role, you will:
- Lead Technical Strategy: Build and lead a team of managers and engineers responsible for core occupancy modeling and rare event detection, driving the team’s roadmap, productivity, and execution.
- Drive Model Evolution: Own the development and deployment of critical perception models, overseeing the consolidation of multi-modal architectures and guiding technical design to enhance detection range, robustness and accuracy.
- Innovate with Advanced ML: Lead the adoption of state-of-the-art computer vision and machine learning techniques—such as foundation models and efficient geometrics representations—to improve performance on long-tail classes and support geofence expansion and fleet size expansion.
- Collaborate on Simulation & Data: Collaborate cross-functionally with simulation and data teams to leverage synthetic data and edge-case scenarios, ensuring the perception system performs reliably in adverse weather and safety-critical environments.
- Ensure Organizational Excellence: Drive organizational health by balancing technical leadership with people management, establishing best practices for data-driven decision-making, and enabling the team to scale effectively.
Qualifications:
- Strong understanding of computer vision systems, AI software stacks, and sensor fusion across multiple modalities.
- 3+ years of technical leadership experience, 10+ years of experience in computer vision, machine learning and related fields.
- Strong leadership skills in recruiting, leading, growing, and managing technical team members in solving challenging problems, and building critical components of a real-time system
- Expertise in implementing autonomy solutions and deploying real-world systems
- Experience with recent AI approaches including VLM, LLM, Transformers and GenAI (3D/4D GS, Diffusion, NeRF).
Bonus Qualifications:
- Familiarity with perception of autonomous vehicles or similar robots
- Hands-on experience having deployed real products or platforms into the real world, and intimately understanding the challenges of working with complex systems
- Involvement in validation or evaluation of risk and/or safety-critical systems