ML Engineer — United States

About The Company

General Motors (GM) is a global leader in the automotive industry, committed to creating a future with Zero Crashes, Zero Emissions, and Zero Congestion. With a strong focus on innovation, GM is at the forefront of developing autonomous vehicle (AV) technologies that are safe, reliable, and scalable. The company’s vision is to lead transformative change through technology, ingenuity, and the creativity of its diverse workforce. GM fosters an inclusive and equitable workplace culture where employees are empowered to contribute to solutions that improve safety and mobility worldwide. The company operates across multiple locations, including Sunnyvale, California, and Seattle, Washington, and supports a hybrid and remote work environment.

About The Role

We are seeking a Staff AI/ML Engineer to join the Embodied AI Data Foundations organization. This role focuses on developing data-centric AI solutions that enhance autonomous driving performance by designing and executing data curation and model training strategies. The successful candidate will work with large-scale real-world and synthetic datasets to improve model behavior and driving safety. Responsibilities include designing experiments to optimize data composition, applying advanced machine learning techniques such as self-supervised learning and reinforcement learning, and collaborating across teams to integrate models into onboard driving systems. This position offers a unique opportunity to impact real-world autonomous vehicle behavior and contribute to pioneering research in embodied AI.

Qualifications

• Master’s or PhD in Computer Science, Robotics, Machine Learning, or a related field.

• Strong fundamentals in machine learning, including experimental design, baseline selection, and ablation analysis.

• Proficiency in Python and PyTorch, with experience training models on large datasets.

• Hands-on experience with data-centric machine learning techniques such as data curation, sampling, labeling, and evaluation.

• Knowledge of large-scale foundation models, including pre-training, fine-tuning, and alignment methods.

• Solid data analysis skills using tools such as NumPy, Pandas, SQL, or Spark.

• Proven ability to deliver applied machine learning solutions under real-world constraints and timelines.

• Excellent communication skills to effectively explain results to both technical and non-technical stakeholders.

• Preferred qualifications include a PhD, publications, or open-source contributions in areas such as representation learning, multimodal models, generative models, reinforcement learning, or data-centric ML.

• Experience with robotics, autonomous driving, embodied AI, synthetic and simulation data, and production ML deployment workflows is highly desirable.

Responsibilities

• Design and conduct experiments linking data composition to model behavior, including dataset mixtures, sampling strategies, curricula, and scaling studies.

• Apply advanced ML methods such as self-supervised pre-training, imitation learning, reinforcement learning, and foundation-model fine-tuning to driving behavior, trajectory generation, and perception tasks.

• Develop data curation and mining techniques including auto-labeling, deduplication, difficulty and uncertainty estimation, and discovery of long-tail and out-of-distribution scenarios.

• Define and implement offline metrics and evaluation frameworks that reliably predict on-road vehicle behavior.

• Analyze model failures to identify data-related root causes and specify corrective data collection strategies.

• Train models at scale using multi-GPU and multi-node systems, collaborating with platform teams to optimize pipelines and tooling.

• Work cross-functionally to integrate models into onboard driving systems and document best practices and lessons learned.

• Stay current with relevant academic literature and incorporate promising advances into modeling and evaluation processes.

Benefits

• Comprehensive benefits package starting from day one, supporting well-being at work and home.

• Opportunities for career development and continuous learning.

• Access to cutting-edge technology and large-scale real-world datasets.

• Collaborative and inclusive work environment fostering innovation and diversity.

• Flexible work arrangements including remote and hybrid options.

• Resources and support for employees with disabilities, including reasonable accommodations.

Equal Opportunity

General Motors is an Equal Employment Opportunity employer committed to fostering an inclusive workplace free from unlawful discrimination. Employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, veteran status, or any other protected status in accordance with applicable laws. GM encourages applicants from diverse backgrounds to apply and provides reasonable accommodations to individuals with disabilities throughout the recruitment process. We believe that an inclusive environment enables our employees to thrive and drives the development of better products for our customers.