Perception Machine Learning Engineer

Build and deploy perception-focused machine learning capabilities for autonomous vehicles using real-world vehicle data.

Responsibilities

• Design machine-learning-based perception systems for autonomous vehicles
• Train, evaluate, and iterate on computer vision models using real-world sensor data
• Create data and experimentation workflows to surface failure modes and improve model performance
• Develop perception capabilities for detection, classification, segmentation, depth estimation, or scene understanding
• Analyze vehicle data and model failure cases to identify weaknesses and prioritize improvements
• Integrate trained models into production perception systems
• Transition new machine learning techniques from experimentation into deployed systems

Requirements

• Python proficiency
• Hands-on experience developing computer vision and/or machine learning systems
• Strong experience with PyTorch or a comparable ML framework
• Solid understanding of computer vision fundamentals and real-world visual data
• Experience evaluating models using quantitative metrics and experimental analysis
• Experience moving ML or computer vision systems into production

Technologies

• Python
• PyTorch
• C++
• ONNX
• TensorRT
• CUDA

Location

• Alameda, CA (onsite)

Compensation

• USD 144,500 - 322,742 per year

Benefits

• Generous Time Off: Competitive Paid Time Off (PTO) accrual, robust annual holiday schedule, and paid sick leave
• Comprehensive Health Coverage: Premium multi-tier Medical, Dental, and Vision plans with significant company contributions for employees and dependents
• Shared Ownership in the Mission: Equity grants
• Retirement Savings: 401(k) with flexible pre-tax and Roth payroll contribution options
• Investment in Your Growth: Annual professional development reimbursement program
• Relocation Support: Relocation assistance for eligible roles

Nice to Have

• C++ experience for production perception systems
• Experience in robotics, autonomous vehicles, aerospace, or defense
• Edge or embedded ML deployment experience
• Sensor fusion, 3D perception, or multimodal perception experience
• ONNX, TensorRT, CUDA, or other inference optimization experience