Machine Learning Engineer, Simulation Scenario Generation

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About this role

Machine Learning Engineer, Simulation Scenario Generation Foster City, CA Do you enjoy applying machine learning to complex, real-world problems in autonomous vehicle testing? The Simulation Scenario Generation team is looking for a ML Engineer to enable next-generation scalable AV scenario creation workflows. This ranges from generating large-scale traffic simulations to extending our agentic AI system to assist in synthetic scenario creation from a natural language test specification. This role offers a unique chance to deliver immediate user impact while contributing to long-term AI-driven safety validation. Do you enjoy applying machine learning to complex, real-world problems in autonomous vehicle testing? The Simulation Scenario Generation team is looking for a ML Engineer to enable next-generation scalable AV scenario creation workflows. This ranges from generating large-scale traffic simulations to extending our agentic AI system to assist in synthetic scenario creation from a natural language test specification. This role offers a unique chance to deliver immediate user impact while contributing to long-term AI-driven safety validation. In this role, you will: - Contribute to tooling for AI-based scenario understanding and validation. - Synthesize realistic AV simulation scenarios with dynamic (e.g., traffic) and static features. - Develop, integrate, and validate ML models (including custom models and off-the-shelf LLMs/VLMs) for complex scenario generation workflows, leveraging techniques like agentic tool use. - Collaborate directly with internal customers and partner teams to provide generative AI solutions for their test creation workflows. - Directly contribute to the safety and reliability of Zoox's autonomous software. Qualifications - MS or PhD in

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