Develop ML models for generating realistic autonomous vehicle simulation scenarios, integrating LLMs/VLMs and agentic AI for safety validation. Requires 5+ years ML experience, MS/PhD, and proficiency in PyTorch, transformers, diffusion models.
233k – 290k/yr
On-site5+ YOEML Engineering
About the role
Responsibilities
Contribute to tooling for AI-based scenario understanding and validation.
Synthesize realistic AV simulation scenarios with dynamic (e.g., traffic) and static features.
Integrate and validate LLMs/VLMs and implement other models 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 Computer Science, Machine Learning, or related field
5+ years of industry experience in Machine Learning
Proficiency in Python and ML libraries (PyTorch, JAX, NumPy, etc.) demonstrated through professional or research projects
Demonstrated experience in transformer and diffusion architectures
Practical experience in dataset creation for fine-tuning, system integration of ML models into production, or optimization techniques for low-latency inference systems
Bonus Qualifications
Familiarity with autonomous vehicles, robotics, and/or complex simulation environments
Hands-on experience in areas like program synthesis and/or formal methods/V&V
Relevant publications in conferences (e.g., CVPR, ICCV, RSS, and/or ICRA)
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