As an Applied ML Validation Manager lead a team to build frameworks for evaluating ML behavior against human driving expectations working closely with various teams to integrate these outputs into validation processes.

Description
Role
As an Applied ML Validation Manager on the Software Validation team within the AV organization you will lead a team focused on building and operating behavior critics and human benchmarking capabilities for ML-driven autonomy systems. Your team will turn subjective human expectations about safe comfortable and intuitive driving into rigorous scalable evaluation frameworks that directly inform model development and release decisions.
You will partner closely with autonomy simulation safety and product teams to define how behavior is judged against human drivers and integrate behavior critic signals into validation pipelines continuous release and long-term performance monitoring.
About the Organization
The Autonomous Vehicle (AV) organization is dedicated to advancing the development of autonomous vehicles through cutting-edge simulation technologies and novel iterative development processes.
The Software Validation team focuses on unlocking software launches and continuous release decisions via simulation-led verification and validation strategies prototypes and protocols. Our collaborative environment fosters innovation and excellence allowing us to push the boundaries of what is possible in autonomous vehicle testing.
Key Responsibilities

• Lead and grow an Applied ML validation team focused on behavior evaluation and human benchmarking for autonomy ML systems.
• Define the strategy and roadmap for evaluating ML behavior against human-like driving expectations across simulation replay and on-road environments.
• Design implement and operate behavior critic frameworks that assess model actions and trajectories turning qualitative human feedback into structured labels metrics and scorecards.
• Develop and scale human benchmarking programs including rater guidelines calibration and quality controls to compare ML system performance against expert and typical human drivers.
• 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.

Basic Qualifications

• 8+ years of experience and MS/PhD in Computer Science Machine Learning Robotics Software Engineering Data Science or a related field.
• 2+ years of people management experience leading engineering validation or applied ML teams.
• Strong programming and data skills in Python and common analysis/ML tooling (e.g. PyTorch).
• Demonstrated experience designing and operating evaluation/validation pipelines for complex ML systems.
• Proven ability to define implement and track metrics that capture system quality reliability safety or user experience.

Preferred Qualifications

• Experience with autonomous driving robotics or other safety-critical domains especially in validation safety or systems engineering roles.
• Demonstrated background with simulation-based validation including VLM critics human benchmarking and scalable evaluation for ML or autonomy systems.
• Hands-on experience with agentic workflows used to accelerate analyses automate documentation or orchestrate complex data and metric pipelines.
• Track record of building or scaling technical teams and tooling in fast-evolving domains especially focused on evaluation automation and ML observability .

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York Colorado California or Washington. • The salary range for this role: is $218000 to $335000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. • Bonus Potential: An incentive pay program offers payouts based on company performance job level and individual performance. • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical dental vision Health Savings Account Flexible Spending Accounts retirement savings plan sickness and accident benefits life insurance paid vacation & holidays tuition assistance programs employee assistance program GM vehicle discounts and more
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