Staff ML Engineer - Embodied AI Onboard Autonomy

General Motors; Mountain View (CA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Company vehicle program

Relocation benefits

Job summary

General Motors is seeking a senior ML engineer to design, develop, and deploy onboard ML models for autonomous driving. You will lead end-to-end projects from concept to onboard implementation, focusing on real-time inference, robustness, and safety-critical operation.

You will advance neural networks, training, and optimization techniques, mentor teams, and collaborate across engineering groups to align ML roadmaps with vehicle product milestones.

Qualifications

• Master's or Ph.D. in Machine Learning, Robotics, Computer Science, Electrical Engineering, or related field.
• 4+ years of experience with large-scale foundation models (LLMs, VLAs, vision models).
• Experience deploying real-time onboard ML systems in safety-critical contexts.
• Proven track record building robust DL models mapping sensor data to actions.
• Strong background in CV techniques, architectures, and real-time inference.

Responsibilities

• Design, develop, and deploy advanced onboard ML models for real-time inference in autonomous driving.
• Lead complex ML projects from conception to onboard implementation with scalability and safety focus.
• Advance architectures, training methods, and inference optimization for onboard use.
• Provide mentorship and raise ML engineering standards across teams.
• Collaborate with multidisciplinary groups to integrate ML into vehicle systems.
• Help shape ML roadmaps aligned with product milestones.

Skills

Advanced degree in ML/CS/EE

Foundation models & LLMs

End-to-end real-time onboard ML

Deep learning model development

Computer vision techniques

Python & C++

PyTorch / TensorFlow / JAX

Communication & mentoring

AV/ADAS experience

Education

Master's or Ph.D. in ML/Robotics/CS/EE

Tools

PyTorch

TensorFlow

JAX

Job description

Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios.

Key Responsibilities

• Drive the design, development, and deployment of advanced onboard ML models, delivering end-to-end solutions capable of real-time inference and robust autonomous driving performance.
• Lead and architect complex machine learning projects, from conception through validation to onboard implementation, emphasizing scalability, robustness, and safety‑critical operation.
• Champion innovation in neural network architectures, training methodologies, and inference optimization strategies suited for real-time onboard deployment.
• Provide technical mentorship and thought leadership, elevating engineering practices, and fostering ML innovation across teams.
• Collaborate closely with multidisciplinary engineering groups, ensuring seamless integration of ML capabilities into autonomous vehicle systems.
• Influence technical roadmaps, shaping strategic ML priorities aligned with company objectives and product milestones.

Skills & Abilities

• Master's or Ph.D. in Machine Learning, Robotics, Computer Science, Electrical Engineering, or a related technical field.
• 4+ years of experience working with large‑scale foundation models, including LLMs, VLAs, and vision‑focused models.
• Extensive experience developing and deploying advanced ML systems, particularly in end‑to‑end real‑time onboard applications.
• Proven track record as a technical expert in developing robust deep learning models that directly map sensor data to actionable outputs within safety‑critical systems.
• Deep expertise in state‑of‑the‑art computer vision techniques, neural architectures, representation learning, real‑time inference, model optimization, and robustness under uncertainty.
• Strong software engineering proficiency, particularly Python and C++, alongside extensive hands‑on experience with modern ML frameworks (PyTorch, TensorFlow, JAX).
• Excellent communication, collaboration, and mentoring abilities, comfortable influencing technical strategy and guiding ML engineering excellence across the organization.
• AV/ADAS experience is a big plus.

Compensation

• The salary range for this role is $180,000 to $280,000. 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.

Hybrid

This role is categorized as hybrid. Successful candidates are expected to report to the Mountain View Technical Center in the Bay Area three times per week, at minimum.

Relocation

This job may be eligible for relocation benefits.

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. Program participants are required to purchase or lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

Non‑Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non‑discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.