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Zoox

Fully electric autonomous ride-hailing service platform

Machine Learning Engineer - 3D Simulation

Computer VisionPosted on Nov 9
Full-time$155k - $239k /yr

About the Job

Requirements

  • At least 3 years of experience with Python and C++ programming and algorithm design.
  • Experience building and extending radiance field machine learning models.
  • Experience with generative models for 3D or video content.
  • Publications or production experience in human-centric 3D vision, 3D reconstruction, or style transfer.
  • Strong mathematical skills and understanding of probabilistic techniques.

Responsibilities

  • Research, implement, and optimize state-of-the-art machine learning approaches to improve 3D simulation variation and fidelity.
  • Collaborate with ML researchers, technical artists, and simulation engineers to bring new ML techniques to the production simulator.
  • Train 4D generative and world models for simulating rare scenarios.
  • Build scalable, usable cloud pipelines for machine learning solutions in 3D simulation.
  • Improve rendering and tooling for generating realistic data at scale.

Desired Qualifications

  • Experience automating 3D content pipelines using applications such as Houdini, Maya, or Blender.
  • Experience in distributed systems and cloud computing platforms.
  • Experience in generative camera, lidar, radar, or LWIR.

About the Company

Zoox

Fully electric autonomous ride-hailing service platform

Zoox designs and operates an autonomous ride-hailing service built around a purpose-built, fully electric vehicle designed specifically for autonomous operation. The vehicle uses advanced sensors, cameras, and AI to navigate complex urban environments, offering a four-passenger interior for comfort. Unlike competitors that retrofit existing cars, Zoox engineers both the vehicle and the service from the ground up, enabling optimized safety, efficiency, and passenger experience through integrated software that optimizes routing and reduces wait times. The company emphasizes safety through extensive testing and regulatory collaboration, and sustainability via electric mobility. The ultimate goal is to provide a smarter, safer, and more efficient urban transportation system that improves city life while reducing emissions.

Company size
5,001-10,000
Company stage
Acquired
Total funding
$1.2B
Headquarters
Menlo Park, CA
Founded
2014

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