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Machine Learning Engineer (3D Sensor Simulation)

Zoox

Skills

Required

  • ML
  • Python
  • PyTorch / TensorFlow
  • diffusion / flow matching / VAEs

Preferred

  • machine learning models
  • lidar / radar / cameras
  • 3D reconstruction
  • 3DGS
  • computer vision
  • NeRFs
  • differentiable rendering
  • robotics
  • Synthetic Data

Join Zoox, a company at the forefront of autonomous vehicle technology. As a Machine Learning Engineer specializing in 3D Sensor Simulation, you will play a crucial role in creating high-fidelity synthetic data for training and testing our AI systems. You will design, train, and validate ML models that improve the realism of simulated sensor data, collaborate with various teams, and mentor engineers and interns. This position offers a range of benefits, including health insurance, paid parental leave, and opportunities for remote work.

About Zoox

Solid understanding of customizing, tuning, and validating ML training pipelines

Responsibilities

  • Design, train, and validate machine learning models to improve the realism of simulated lidar, radar, and camera data in autonomous vehicle simulation pipelines.
  • Collaborate with Synthetic Data and HIL Sim teams to 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.

Requirements

  • 3+ years of experience developing ML models in Python with PyTorch or TensorFlow
  • You do not need to match every listed expectation to apply for this position
  • Experience with generative techniques such as diffusion, flow matching, or VAEs

Preferred

  • Industry experience applying ML to sensor data (lidar, radar, and/or cameras)
  • Experience with 3D reconstruction (3DGS, NeRFs) or differentiable rendering
  • Prior experience developing autonomy in AVs or other robotics and computer vision

Pay

USD 189,000 - 283,000