Zoox
Overview
The following information provides an overview of the skills, qualities, and qualifications needed for this role. Join to apply for the
Machine Learning Engineer - Generative AI
role at
Zoox .
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.
Responsibilities
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 to deployment.
Design effective model architectures and sophisticated training techniques, leveraging 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.
Qualifications
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)
Bonus Qualifications
Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
Experience with autonomous robotics systems
Experience implementing 4D Gaussian Splatting
Compensation Base salary range: $204,000 - $277,000 per year. Zoox also offers equity in stock options (RSUs) and other compensation components. A sign-on bonus may be offered. Compensation varies by location and level.
Benefits Zoox offers a comprehensive benefits package, including paid time off (sick leave, vacation, bereavement), health insurance, long-term and short-term disability insurance, life insurance, and other benefits. Details may vary by location.
Details
Seniority level: Not Applicable
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Automotive
Location Foster City, CA
#J-18808-Ljbffr
The following information provides an overview of the skills, qualities, and qualifications needed for this role. Join to apply for the
Machine Learning Engineer - Generative AI
role at
Zoox .
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.
Responsibilities
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 to deployment.
Design effective model architectures and sophisticated training techniques, leveraging 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.
Qualifications
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)
Bonus Qualifications
Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
Experience with autonomous robotics systems
Experience implementing 4D Gaussian Splatting
Compensation Base salary range: $204,000 - $277,000 per year. Zoox also offers equity in stock options (RSUs) and other compensation components. A sign-on bonus may be offered. Compensation varies by location and level.
Benefits Zoox offers a comprehensive benefits package, including paid time off (sick leave, vacation, bereavement), health insurance, long-term and short-term disability insurance, life insurance, and other benefits. Details may vary by location.
Details
Seniority level: Not Applicable
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Automotive
Location Foster City, CA
#J-18808-Ljbffr