AI/ML Staff Researcher

General Motors•Mountain View, CA

1d•Hybrid

About The Position

General Motors Global Research and Development is seeking a highly strategic and technically exceptional AI/ML subject matter expert to lead advanced work in Artificial Intelligence, Machine Learning, Large Language Models (LLMs), and Scientific Machine Learning (SciML). This role requires a rare combination of deep technical depth and strong executive presence. You will work hands-on to architect, build, deploy, and scale AI/ML models that address complex engineering and research challenges. At the same time, you will help define strategy, communicate opportunities and risks to leadership, and guide the organization on where and how AI can create the greatest value. The ideal candidate is equally comfortable developing production-grade AI/ML solutions, evaluating emerging technologies, and engaging senior leaders in clear, actionable discussions on strategy, roadmap, and business impact. This is a dual role for someone who can both execute technically at a very high level and influence direction as a thought leader and communicator.

Requirements

US Citizenship required
PhD or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Engineering, Physics, or a related field, with significant relevant experience.
Demonstrated success building and deploying AI/ML models in production or high-value applied research environments.
Deep expertise across multiple AI domains, including machine learning, deep learning, LLMs, generative AI, and physics-based or scientific machine learning.
Strong understanding of modern AI/ML development workflows, including data pipelines, model training, evaluation, deployment, monitoring, and lifecycle management.
Experience applying AI/ML to complex technical domains such as engineering, simulation, scientific computing, and advanced product development.
Proven ability to communicate technical strategy and recommendations effectively to executive leadership.
Track record of leading technically significant initiatives through influence, expertise, and cross-functional collaboration.
Strong verbal and written communication skills, with the ability to tailor messaging to both technical and non-technical audiences.
Ability to balance long-term strategic thinking with near-term execution and delivery.

Nice To Haves

Experience applying AI/ML in automotive, mobility, industrial, defense, or other advanced engineering environments.
Expertise in physics-based AI, scientific machine learning, digital engineering, or hybrid modeling approaches.
Demonstrated success shaping technical roadmaps or AI strategy for large organizations.
Background working directly with senior executives to define direction, prioritize investments, and communicate outcomes.
Strong record of innovation, including patents, publications, or high-impact internal technical contributions.
Experience in mentoring technical teams and early career researchers and engineers.

Responsibilities

Build, validate, deploy, and scale AI/ML models for high-impact engineering, research, and product development applications.
Lead technical work across a broad set of AI domains, including classical machine learning, deep learning, GenAI, Large Language Models, multimodal AI, and physics-based AI.
Translate business and engineering problems into practical AI/ML solution strategies and executable technical plans.
Serve as a technical authority on model development, deployment architectures, data strategy, evaluation methods, and responsible AI practices.
Provide strategic guidance to leadership on AI technology choices, investment areas, roadmap priorities, and capability development.
Communicate complex technical concepts, tradeoffs, and recommendations clearly and effectively to executive and non-technical audiences.
Partner closely with engineering, product, and software teams to transition AI concepts into deployed solutions.
Evaluate emerging AI technologies and identify where they can strengthen GM’s technical portfolio and long-term competitive advantage.
Mentor technical teams and influence best practices in applied AI/ML development, experimentation, deployment, and governance.
Contribute to thought leadership through technical reviews, publications, invention disclosures, and cross-functional collaboration.