Tech Stack

Description

You will deploy, optimize, and maintain ML-driven motion planning and control algorithms for real-time autonomous driving, collaborating across teams to ensure models run reliably under strict performance and safety constraints on vehicle platforms.

Requirements

• BS/MS/PhD in Robotics, CS, EE or related field
• 5+ years deploying ML systems in real-world robotics or autonomous platforms
• Strong C++ and Python skills with modern development practices
• Experience with PyTorch or TensorFlow and model optimization for deployment
• Familiarity with GPU acceleration or inference optimization (e.g., TensorRT, CUDA)

Responsibilities

• Deploy ML-based motion planning and control models onto vehicle platforms under resource constraints
• Optimize models for inference speed, latency, and memory footprint
• Collaborate with planning, controls, and perception teams to integrate ML components
• Build scalable deployment infrastructure including evaluation pipelines and benchmarking
• Validate model performance in simulation and on-road testing