Machine Learning Engineer - 3D Sensor Simulation

Foster City, CA / Seattle, WA Software – Software Systems /Full-time /Hybrid The Zoox 3D Sensor Simulation team’s work is at the core of creating in-the-loop simulation and high fidelity synthetic data for training and testing autonomous vehicle AI. We are looking for a machine learning professional with experience applying ML to sensor data, such as LiDAR, radar, and cameras.

This role lies at the intersection of machine learning and 3D simulation at Zoox, ranging from learned sensor models to neural 3D reconstruction. By improving the realism of simulated sensors (lidar, radar, and cameras), you’ll enable the Zoox robotics autonomy stack to learn, improve, and enhance the mobility of  this role, you will:

Design, train, and validate ML models that improve the realism of simulated lidar, radar, and camera data in autonomous vehicle (AV) simulation pipelines.

Collaborate with Synthetic Data and HIL Sim teams to integrate 3

DGS and NeRF-based 3D reconstruction with simulation of all sensor modalities.

Build and curate training datasets from real and simulated sensor data, including GenAI-based data augmentation.

Partner with Sim V&V and Perception engineers to define sensor realism metrics and close the sim-to-real gaps with the greatest impact on autonomy.

Mentor engineers and interns, and establish best practices for training and deploying ML on Zoox sensor data.

Qualifications:

3+ years of experience developing ML models in Python with PyTorch or Tensor Flow Industry  experience applying ML to sensor data (lidar, radar, and/or cameras)
Solid understanding of customizing, tuning, and validating ML training pipelines

Bonus

Qualifications:

Experience with generative techniques such as diffusion, flow matching, or VAEsExperience with 3D reconstruction (3

DGS, NeRFs) or differentiable rendering

Prior experience developing autonomy in AVs or other robotics and computer vision $189,000 - $283,000 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 Linked In 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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.