The Applied ML Validation Manager role at GM involves leading a team responsible for developing frameworks that evaluate ML-driven autonomy systems based on human benchmarks. The position emphasizes collaboration across various teams to enhance validation pipelines and ensure the safety and reliability of autonomous vehicle technologies
Job Summary
Lead a team focused on building and operating behavior critics and human benchmarking capabilities for ML-driven autonomy systems.
Define the strategy and roadmap for evaluating ML behavior against human-like driving expectations across simulation, replay, and on-road environments.
Partner closely with autonomy, simulation, safety, and product teams to integrate behavior critic and human benchmarking outputs into training, offline validation, release gating, and reporting.
Matching Summary
Match Score: 85
The Applied ML Validation Manager role at GM involves leading a team responsible for developing frameworks that evaluate ML-driven autonomy systems based on human benchmarks. The position emphasizes collaboration across various teams to enhance validation pipelines and ensure the safety and reliability of autonomous vehicle technologies.
Skills & Requirements
Must-have
Applied ML validation team leadership
Behavior evaluation and human benchmarking
ML-driven autonomy systems
Python and common ML tooling
Design and operate evaluation pipelines
Nice-to-have
Autonomous driving experience
Simulation-based validation experience
Agentic workflows for automation
Scaling technical teams and tooling
Key Requirements
8+ years experience and MS/PhD
2+ years people management experience
Strong programming and data skills in Python
Experience designing and operating evaluation pipelines