Machine Learning Engineer, Zoox

• MS or PhD in Computer Science, Machine Learning, or related technical field with 3+ years of industry experience
• Demonstrated experience architecting, training and deploying large models such as diffusion, flow matching, GANs and/or NeRFs
• Experience building and maintaining ML training pipelines, including data preprocessing, model training, and evaluation
• Proficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects
• Experience training with large scale datasets (e.g. tens of millions of videos)

Desirable

• The Perception team at Zoox is at the forefront of leveraging GenAI to create synthetic data, unlocking scalable training and evaluation for our autonomous system's perception and entire stack
• As a Generative AI Engineer, you will develop and train cutting-edge models for sensor-level scenario generation, utilizing world models and radiance fields techniques with large-scale proprietary data
• This role directly impacts the productivity, safety, and capabilities of Zoox's autonomous system by validating algorithms in real-world conditions
• Define and execute the ML roadmap for synthetic data generation using generative AI, evolving both model and infrastructure to meet the training and evaluation needs of Zoox’s autonomous driving solution
• Lead the development of generative models from small scale objects to complete scenarios, from research all the way to deployment
• Design effective model architectures and sophisticated training techniques, leveraging all the inputs from our sensor stack and the overall large scale data we have at Zoox
• Collaborate with perception, planning, safety, simulation, and systems teams to integrate your models into our offline pipelines
• Validate and optimize your solutions using real-world driving scenarios, directly contributing to the safety and reliability of Zoox's autonomous system