Engineer Manager - Perception, Self-Driving Systems

Job description

Job responsibilities

• Own the perception model end-to-end: architecture, training, evaluation, and deployment. The core challenge is building a model that generalizes across geographies, road types, sensor setups, and environmental…
• Drive a camera-first perception strategy. The goal is to progressively reduce dependencies on HD maps and lidar. How to get there is part of the job.
• Lead training and iteration cycles hands-on. You will be in the data, the eval dashboards, and the failure analysis. When perception regresses in a new geography or road type, you own understanding why and fixing it.
• Own model performance across the full deployment surface: highway, urban, residential, ramps, complex intersections, poor weather, hilly terrain. You care about on-vehicle driving outcomes, not just offline metrics.
• Manage the model lifecycle from training through quantization and deployment on embedded compute, including device-specific optimizations.
• Work directly with OEM customer programs to understand sensor configurations, target ODDs, and performance requirements. Translate these into model architecture and data strategy.
• Recruit, develop, and technically lead a team of perception engineers. Set high technical standards and create a culture of rigorous experimentation and measurement.

Job requirements

• Bachelors degree in any field, or equivalent combination of education and work experience.
• 5+ years in ML/deep learning for perception or 3D scene understanding. Deep hands-on experience training and deploying vision models at scale.
• 2+ years managing a perception team, with ability to both set direction and contribute to architecture and training decisions directly.
• Experience building production perception systems, especially camera-only or camera-first solutions.
• Track record deploying perception models to embedded hardware under real-time latency and compute constraints, including device-specific optimizations.
• Strong software engineering in Python and C++, comfortable across the stack from training code to onboard inference integration.
• Experience scaling perception models across multiple geographies, sensor setups, or vehicle platforms.