Senior / Staff Machine Learning Engineer - 3D Sensor Simulation

The role

You will design, train and validate ML models that make simulated lidar, radar and camera data more realistic for autonomous vehicle simulation. You will work with Synthetic Data, HIL Sim, Sim V&V and Perception teams, and mentor engineers and interns.

What you will do

• Design, train and validate ML models that improve realism of simulated lidar, radar and camera data
• Integrate 3DGS 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
• 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

Required qualifications

• 2+ years of prior experience as a Technical Lead
• 5+ years of experience developing ML models in Python with PyTorch or TensorFlow
• Industry experience applying ML to sensor data (lidar, radar, and/or cameras)
• Solid understanding of customizing, tuning and validating ML training pipelines

Nice to have

• Experience with generative techniques such as diffusion, flow matching or VAEs
• Experience with 3D reconstruction (3DGS, NeRFs) or differentiable rendering
• Prior experience developing autonomy in AVs or other robotics and computer vision

Before you apply

• You do not need to match every listed expectation to apply

About the company

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem to bring it to market. It aims to provide next-generation mobility-as-a-service in urban environments.