Zoox
9 hours ago

Senior/ Staff Machine Learning Engineer - Generative AI

Job Description

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.
Base Salary Range

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.

Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

In this role, you will:

  • 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
  • ,

    Qualifications:

  • MS or PhD in Computer Science, Machine Learning, or related technical field
  • 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
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