Machine Learning Engineer Intern - Scenario Generation

About the role#

As a Machine Learning Engineer Intern on the Simulation team, you will explore and prototype a generative simulator capable of synthesizing diverse, realistic driving scenarios. You will work on creating scenarios conditioned on map, traffic, and ego-vehicle state to stress-test the vehicle's on-board modules against rare or safety-critical events.

What you'll do#

• Evaluate existing open-source generative simulators and scenario generators for fidelity and efficiency to determine the best baseline.
• Ingest and process internal, real-world driving logs to fine-tune the model.
• Connect the prototype to the data pipeline to ingest map data and output structured scenarios.
• Translate generated scenarios into the standardized formats required by the company’s simulation engine.
• Develop metrics to validate the physical realism, diversity, and kinematic feasibility of the generated scenarios.
• Collaborate with ML researchers, simulation engineers, and on-board teams to define scenario requirements.

What you'll need#

• Solid Python programming skills.
• Familiarity with deep learning frameworks, with a preference for PyTorch.
• Basic understanding of generative models, such as VAEs, GANs, or diffusion models.
• Experience working with datasets, including loading and preprocessing.
• Pursuing a degree in Computer Science, Data Science, or Computer Engineering.

Location & details#

• Location: Santa Clara, California.
• Term: Summer 2026.
• Modality: On-site.
• Commitment: Full-time.
• Compensation: This is a paid internship.