Staff ML Engineer - Embodied AI Onboard Autonomy

General Motors; Sunnyvale (CA); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Relocation benefits

Company vehicle program

Job summary

General Motors seeks a Staff AI/ML Engineer for the Onboard Embodied AI team to advance real-time ML for autonomous driving. You will architect end-to-end ML solutions translating sensor data into driving actions, mentoring engineers and steering strategic ML initiatives.

You will lead complex projects, collaborate with cross-functional groups, optimize models for safety-critical operation, and drive innovative neural architectures and deployment strategies for real-world scenarios.

Qualifications

• Master’s or Ph.D. in ML, Robotics, CS, or EE.
• 4+ years with large-scale Foundation Models including LLMs, VLAs and vision models.
• Extensive experience building and deploying end-to-end real-time onboard ML systems.
• Proven track record delivering robust DL models mapping sensor data to actionable outputs in safety-critical contexts.
• Deep expertise in CV techniques, neural architectures, representation learning, real-time inference, and robustness.
• Strong software skills in Python and C++, with PyTorch/TensorFlow/JAX experience.
• Excellent communication, collaboration and mentoring abilities across teams.
• AV/ADAS experience is a big plus.

Responsibilities

• Drive design, development and deployment of advanced onboard ML models for real-time inference and safety-critical performance.
• Lead and architect complex ML projects from concept to onboard implementation.
• Champion innovations in neural architectures and inference optimization for real-time deployment.
• Provide mentorship and technical leadership across ML teams.
• Collaborate with multidisciplinary groups to integrate ML into autonomous vehicle systems.
• Influence ML roadmap and priorities aligned with product milestones.

Skills

Foundation Models

Real-time onboard ML

Python

C++

PyTorch

TensorFlow

Neural Networks

Mentoring

AV/ADAS experience

Education

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

Tools

PyTorch

TensorFlow

JAX

Job description

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.

As a Staff AI/ML Engineer within the Onboard Embodied AI organization, you will be a senior individual contributor driving cutting-edge end-to-end machine learning solutions directly impacting autonomous driving performance. Your role is pivotal in designing, architecting, and deploying advanced ML models that translate raw sensor data into actionable driving behaviors, enabling vehicles to robustly navigate diverse real-world scenarios and conditions. You'll lead critical technical initiatives, collaborate closely with cross-functional teams, mentor ML engineers, and significantly shape the future of onboard ML capabilities.

The Onboard Embodied AI team is at the forefront of developing groundbreaking onboard ML systems powering fully autonomous vehicles. We leverage modern end-to-end machine learning approaches with sophisticated neural networks trained from large-scale driving data and using state-of-the-art alignment approaches. Our solutions enable vehicles to understand complex, dynamic driving environments, handle uncertainty gracefully, and adapt seamlessly to changing conditions. Join a collaborative and innovative team redefining autonomy through state-of-the-art machine learning, delivering solutions that move beyond current technological boundaries.

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.

Your 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 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 $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. This means the successful candidate is 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. 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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About GM

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