Applied ML/AI Manager - Behavior Validation

General Motors; United States; Hybrid; USD 219,000 - 335,000; Full time

Benefits offered by this job

Company vehicle program

Relocation benefits

Job summary

General Motors is seeking an Applied ML/AI Manager - Behavior Validation within the AV organization. You will lead a cross-functional team building and operating behavior critics and benchmarking for ML-driven autonomy, turning human expectations into scalable evaluation frameworks that guide development and release decisions.

Ideal candidates have 8+ years of experience with a PhD or MS in a relevant field, strong Python/PyTorch skills, and a track record deploying ML pipelines in production.

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 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 and product milestones.
• Partner closely with autonomy, simulation, safety, and product teams to integrate these models into the validation ecosystem of autonomous vehicles.

Skills

Python

PyTorch

Leadership

ML Deployment

Data Science

Education

MS/PhD in CS/ML/Robotics/Software Eng/Data Science

Job description

Job 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.

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 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.

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 About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources .

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