About this role

Integrate and validate LLMs/VLMs and implement other models for complex scenario generation workflows, leveraging techniques like advanced prompting, agentic tool use, and more.
Contribute to tooling for AI-based scenario understanding and validation.
Collect data and design metrics to drive business intelligence, product iteration, and model fine-tuning.
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.

MS or PhD in Computer Science, Machine Learning, or related field
2+ years of industry experience in Machine Learning
Solid understanding of LLM or NLP concepts
Proficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects
Practical experience in dataset creation for fine-tuning, system integration of ML models into production, or optimization techniques for low-latency inference systems
Familiarity with autonomous vehicles, robotics, and/or complex simulation environments
Hands-on experience in areas like program synthesis, diffusion models, and/or formal methods/V&V
Relevant publications in conferences (e.g., CVPR, ICCV, RSS, and/or ICRA)

Machine Learning Engineer – Simulation Scenario Generation

Key skills