Job Description

Staff Technical Program Manager, Embodied AI

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard – from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.

Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

The Role

You will serve as a Staff Technical Program Manager responsible for end-to-end delivery of Embodied AI (EAI) model development programs – from research integration through production deployment on next-generation autonomy platforms.

In this role, you operate at the intersection of AI research, engineering execution, and product delivery. You translate complex, ML-heavy development efforts into disciplined, predictable execution that results in production-quality systems used in real vehicles, at scale.

Why This Role Matters

This role defines how GM builds and ships AI.

You will own:

The execution systems that power Embodied AI development
The cross‑functional delivery of major AI model initiatives

Your impact is direct and measurable: you enable GM’s ability to deliver world‑class autonomy and AI‑driven vehicle intelligence.

As a Staff TPM, you will drive execution for highly visible, technically complex programs with significant cross‑functional and executive exposure. You influence AI strategy, define execution rhythms across teams, and ensure Embodied AI systems meet performance, safety, quality, and readiness standards for L2+ and L4 autonomy.

Examples of initiatives you will own or lead within the Embodied AI domain include:

Driving execution of model training, evaluation, and performance improvement initiatives for AV and ADAS features by partnering across ML, data, evaluation, and platform teams to deliver measurable gains against product and safety targets.
Leading end‑to‑end programs for fallback capabilities, ensuring robust Primary, Secondary, and Tertiary detection and behavioral features that support safe operation across both nominal and off‑nominal conditions.
Owning delivery of ML platforms and training systems that improve developer velocity across the full model lifecycle – from data ingestion and training to evaluation, deployment, and iteration.
Coordinating localization, sensor alignment, and calibration programs critical to high‑quality sensor data ingestion and downstream ML performance, working closely with perception, mapping, data, and vehicle platform teams.
You will also own the operating mechanisms, milestones, and execution frameworks that accelerate Embodied AI development while ensuring models land with the quality, reliability, and efficiency required to scale across multiple platforms and product lines.

What You’ll Do

Own End-to-End Model Development Execution

Own execution across the full Embodied AI model lifecycle, from research transition and model training through evaluation, system integration, validation, and production release.
Drive milestone readiness across model training cycles, performance gates, SC3 program milestones, and feature maturity reviews.
Partner closely with AI/ML, Evaluation, and Product leads to define clear success criteria, performance metrics, and evaluation frameworks that align technical progress to product outcomes.
Deliver clear, concise, and executive‑ready communication on program status, risks, dependencies, and decisions to senior GM leadership.

Build and Scale Execution Processes for EAI

Design, implement, and operate execution mechanisms that enable faster, more predictable Embodied AI delivery, including:
- Planning and execution cadences
- KPI‑driven performance reporting and dashboards
- Model training, evaluation, and release workflows
- Issue escalation, dependency management, and risk mitigation processes
Standardize how Embodied AI initiatives are defined, planned, measured, and delivered across teams and programs.
Ensure engineering teams have the data, tooling, clarity, and operational rigor needed to hit performance targets with speed and consistency, without compromising quality or safety.

Your Skills & Abilities (Required Qualifications)

Bachelor’s degree in Computer Science, Engineering, Robotics, or a related technical field, or equivalent practical experience.
8+ years of experience in technical program management, engineering program leadership, or closely related roles within software‑ or ML‑intensive environments.
Proven track record of leading large‑scale AI/ML, autonomy, or complex software system programs from early concept through production deployment.
Strong working knowledge of modern model development workflows, including data ingestion and curation, model training pipelines, evaluation and metrics, deployment, and iteration.
Demonstrated ability to operate effectively in highly cross‑functional environments, influencing senior engineering, product, and research leaders to drive execution, resolve tradeoffs, and align priorities.
Exceptional communication skills, with the ability to translate complex technical execution into clear, executive‑level narratives around progress, risks, and decisions.

What will give you a competitive edge (Preferred Qualifications)

MS or PhD in Engineering, Computer Science, Robotics, Machine Learning, Applied Mathematics, or a related field.
Experience working on autonomous driving, ADAS, robotics, or other safety‑critical systems.
Familiarity with large‑scale ML infrastructure, including distributed training, compute optimization, data scaling, or evaluation tooling.
Experience defining operating rhythms, KPIs, and execution frameworks for ML‑heavy or research‑driven engineering organizations.

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 actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate.

The salary range for this role is $159,400 - $245,000. 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.

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.

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This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

This job may be eligible for relocation benefits.



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

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Benefits Overview

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