Software Engineering Manager - Perception Occupancy

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