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Gen AI Staff Researcher
General Motors. Contribute original research and technical expertise to generative world models, focusing on diffusion-based modeling of driving environments and dynamics .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Expertise in generative AI and diffusion models, with a strong focus on designing, training, and evaluating large-scale models for multimodal data. Proven ability to optimize distributed training processes and contribute to impactful research in autonomous driving.
Highest-signal resume keywords
PhD In Computer ScienceGenerative AI Research ExperienceDiffusion Model ExpertiseLarge-Scale Distributed TrainingPython Coding Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Generative AIDiffusion ModelsMachine LearningComputer VisionTraining OptimizationWorld ModelingSpatiotemporal LearningData CurationEvaluation MethodsMultimodal Generation
Tools & Technologies
PyTorchMulti-GPU Infrastructure
Industry Keywords
Autonomous DrivingResearch PublicationSimulationSynthetic Data GenerationTemporal Consistency
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Contribute original research and technical expertise to generative world models, focusing on diffusion-based modeling of driving environments and dynamics
- Design, build, train, and evaluate large-scale diffusion models for video and multimodal generation
- Emphasize temporal consistency, physical plausibility, and controllability
- Implement and optimize large-scale training on distributed, multi-GPU infrastructure
- Improve training stability, throughput, memory efficiency, and scalability
- Develop action- and context-conditioned world models for future scenarios, counterfactual exploration, closed-loop simulation, and long-tail scenario coverage
- Develop and evaluate data and training strategies for fleet-scale datasets, including data curation, pretraining, fine-tuning, and targeted generation of challenging driving scenarios
- Apply rigorous evaluation methods connecting generative quality, consistency, and scenario coverage to downstream autonomous-driving KPI improvements
- Collaborate with engineering teams to translate research into scalable solutions for simulation, synthetic data generation, and autonomy development
- Publish research at top-tier conferences and journals
- Track advances in generative AI and incubate technologies impacting L3 autonomous driving
Requirements
What you’ll need- PhD in Computer Science, Electrical Engineering, Robotics, or a related field; excellent M.Sc. graduates will be considered
- Over 3 years of research experience in generative AI, computer vision, machine learning, or related areas
- Demonstrated depth of expertise and impactful contributions to complex research projects
- Deep expertise in diffusion models and hands-on experience designing, training, and evaluating generative models for images, video, or multimodal data
- Hands-on experience with large-scale distributed training of deep learning models, including training stability, performance optimization, and systematic experimentation
- Strong understanding of world modeling and spatiotemporal learning, including temporal consistency, conditioning mechanisms, and learning environment dynamics
- Strong publication record at top-tier AI/ML conferences and journals
- Excellent coding skills in Python
- Proficiency with modern AI frameworks such as PyTorch
Benefits
Comp & perks- Role-related assessment(s) and/or pre-employment screening may be required
- Reasonable accommodations available for applicants with disabilities