Description Work Arrangement:

This role is categorized as Remote/ hybrid .

Remote:

This role is based remotely but if you live within a 50-mile radius of [Austin, Detroit, Warren, Milford, Sunnyvale, CA ], you are expected to report to that location three times per week, at minimum. The Role As an Applied ML/AI Manger - Behavior Validation 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. What You'll Do 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 and product milestones. Partner closely with autonomy, simulation, safety, and product teams to integrate these models into the validation ecosystem of autonomous vehicles. Your Skills & Abilities (Required Qualifications) 8+ years of experience and MS/PhD in Computer Science, Machine Learning, Robotics, Software Engineering, Data Science , or a related field. Strong programming and data skills in Python and PyTorch Demonstrated experience fine-tuning and deploying to production vision-based and/or time series-based ML/AI pipelines. 2+ years of people management or tech lead experience leading engineering teams. What Will Give You a Competitive Edge (Preferred Qualifications) Experience with autonomous driving, robotics, or other safety-critical domains , especially in perception, prediction, planning, validation, safety, or systems engineering roles. Experience designing and training foundation models . Demonstrated background with simulation-based validation for autonomy systems.

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 the California Bay Area. The salary range for this role is ($218,800 - $335,300). 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.

Company Vehicle :

Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate.

Note:

program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies. This Job may be eligible for relocation benefits. #LI-SA2 This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}. The selected candidate will be required to travel