General Motors
General Motors
General Motors is a global automotive and manufacturing company working across vehicle engineering, production, transportation, and information technology. Founded in 1908, GM develops technologies aimed at advancing mobility while pursuing its vision of zero crashes, zero emissions, and zero congestion. Its international operations bring together large, multidisciplinary teams focused on innovation, sustainable transportation, and the future of the automotive industry.

Staff Generative AI Researcher, World Models

Lead research into diffusion-based world models for General Motors’ autonomous vehicles. Advance generative AI, simulation, and Level 3 autonomy through large-scale research.

Description

  • Conduct original research on diffusion-based world models of driving environments and dynamics.
  • Design, train, and evaluate large-scale diffusion models for video and multimodal generation.
  • Prioritize temporal consistency, physical plausibility, and controllability in generated outputs.
  • Build and optimize large-scale training across distributed, multi-GPU systems.
  • Improve training stability, throughput, memory use, and scalability.
  • Create action- and context-conditioned world models for future scenarios, counterfactual exploration, closed-loop simulation, and long-tail scenario coverage.
  • Develop and assess data and training approaches for fleet-scale datasets, including curation, pretraining, fine-tuning, and targeted generation of challenging driving scenarios.
  • Use rigorous evaluations to connect generative quality, consistency, and scenario coverage with downstream autonomous-driving KPI gains.
  • Work with engineering teams to turn research into scalable tools for simulation, synthetic data generation, and autonomy development.
  • Publish research in leading conferences and journals.
  • Monitor generative AI advances and develop technologies relevant to Level 3 autonomous driving.

Requirements

  • PhD in Computer Science, Electrical Engineering, Robotics, or a related discipline; exceptional M.Sc. graduates may also be considered.
  • More than three years of research experience in generative AI, computer vision, machine learning, or a related field.
  • Evidence of deep expertise and meaningful contributions to complex research projects.
  • Strong diffusion-model expertise and practical experience designing, training, and evaluating generative models for images, video, or multimodal data.
  • Practical experience training deep learning models at scale across distributed systems, including stabilizing training, optimizing performance, and conducting systematic experiments.
  • Strong grasp of world modeling and spatiotemporal learning, including temporal consistency, conditioning methods, and learning environmental dynamics.
  • Strong publication history in leading AI/ML conferences and journals.
  • Excellent Python programming skills.
  • Proficiency with modern AI frameworks, including PyTorch.

Benefits

  • Role-related assessments and/or pre-employment screening may be required.
  • Reasonable accommodations are available to applicants with disabilities.

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