Applied ML/AI Manager – AV Behavior Validation (Remote)

generalmotors; Sunnyvale (CA); Hybrid; USD 219,000 - 335,000; Full time

Benefits offered by this job

Company vehicle program

Relocation benefits

Bonus potential

Job summary

General Motors seeks an Applied ML/AI Manager - Behavior Validation to lead a cross-functional team evaluating behavior and benchmarking for autonomous vehicle systems. You will design offboard ML models for behavioral inference and shape roadmaps aligned with product milestones.

Collaborating with autonomy, simulation, safety, and product teams, you will integrate signals into validation pipelines and drive continuous release and long-term performance monitoring.

Qualifications

• 8+ years of experience and MS/PhD in CS, ML, robotics, software engineering, data science, or related field.
• Strong programming and data skills in Python and PyTorch.
• Experience fine-tuning and deploying to production vision-based and time-series ML/AI pipelines.
• 2+ years of people management or tech lead experience leading engineering teams.

Responsibilities

• Lead and grow a cross-functional team focused on behavior evaluation and human benchmarking for autonomous vehicles.
• Design, implement, and operate offboard ML models capable of robust behavioral inference.
• Architect technical roadmaps, shaping strategic ML priorities aligned with company objectives.
• Partner with autonomy, simulation, safety, and product teams to integrate models into validation ecosystems.

Skills

Leadership

Python

PyTorch

ML pipelines

Education

MS/PhD in Computer Science, ML, Robotics, Software Engineering, or Data Science

Tools

Python

PyTorch

Job description

General Motors seeks an Applied ML/AI Manager - Behavior Validation to lead a cross-functional team evaluating behavior and benchmarking for autonomous vehicle systems. You will design offboard ML models for behavioral inference and shape roadmaps aligned with product milestones.

Collaborating with autonomy, simulation, safety, and product teams, you will integrate signals into validation pipelines and drive continuous release and long-term performance monitoring.