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Machine Learning Engineer, 3D Simulation
Machine Learning Engineer, 3D SimulationZoox • Foster City, CA, United States
Machine Learning Engineer, 3D Simulation

Machine Learning Engineer, 3D Simulation

Zoox • Foster City, CA, United States
30+ days ago
Job type
  • Full-time
Job description

The 3D Simulation group at Zoox is looking for machine learning engineers to bring the latest research in 3D vision to improve diversity and blur the line between simulation and reality. You will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. Our ML group is working on generating rich and diverse 3D environments, humans, and environmental conditions, and you will be able to contribute to all of these.

In this role, you will :

  • Research, implement, and optimize state of the art machine learning approaches to improve simulation variation and fidelity
  • Collaborate with ML Researchers, Technical Artists and Simulation engineers to bring new ML techniques to our production simulator
  • Build scalable, useable cloud pipelines for machine learning solutions in 3D simulation
  • Improve rendering and tooling for generating realistic data at scale

Qualifications :

  • 3+ years of experience with programming and algorithm design
  • Fluency in Python and C++
  • Experience building and extending radiance field ML models
  • Publications or production experience in human-centric 3D vision, 3D reconstruction, or style transfer
  • Strong mathematical skills and understanding of probabilistic techniques
  • Bonus Qualifications :

  • Bachelor's, Master's or PhD in computer science, mathematics, physics, or related field
  • Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
  • Experience with generative models for 3D or video content
  • Experience automating 3D content pipelines using applications like Houdini, Maya, or Blender
  • Experience in distributed systems and cloud computing platforms
  • Experience in generative camera, lidar, radar, or LWIR
  • $151,000 - $257,000 a year

    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.

    About Zoox

    Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

    Follow us on LinkedIn

    Accommodations

    If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

    A Final Note :

    You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

    We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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    Machine Learning Engineer • Foster City, CA, United States

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