Zoox is looking to integrate, implement, and optimize their next-generation AV scenario generation workflow using machine learning to advance toward full scenario creation automation from natural language test specification.
Requirements
- 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
Responsibilities
- 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.
Other
- MS or PhD in Computer Science, Machine Learning, or related field
- 2+ years of industry experience in Machine Learning
- Relevant publications in conferences (e.g., CVPR, ICCV, RSS, and/or ICRA)
