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ZooxZooxFoster City, CA

Machine Learning Engineer - 3D Sensor Simulation

Develops and optimizes ML-driven 3D sensor simulations (cameras, lidar, radar) using GenAI and graphics techniques to generate realistic synthetic data for AV testing. Requires 2+ years experience with neural rendering (NeRFs, Gaussian Splatting), PyTorch/TensorFlow, Python/C++, and 3D math.

176k – 257k
Hybrid2+ YOEML Engineering

About the role

Responsibilities

  • Research, implement, and optimize state-of-the-art 3D rendering of sensor data, leveraging GenAI/ML and 3D graphics.
  • Develop realism metrics with V&V to show measurable impact of improved sensor fidelity.
  • Collaborate with Perception and Safety teams to improve realism of sensor simulation for high-fidelity synthetic data.
  • Improve rendering and ML inference tooling for generating realistic data at scale.

Qualifications

  • 2+ years of industry experience, and/or PhD, developing neural rendering techniques like Gaussian Splatting, NeRFs, or 3D reconstruction.
  • 2+ years of experience developing software with Python and/or modern C++.
  • Expertise with machine learning frameworks PyTorch or TensorFlow.
  • Familiarity with 3D graphics algorithms, such as 3D geometry and camera models.
  • Strong mathematical skills and understanding of 3D linear algebra and probabilistic techniques.

Bonus Qualifications

  • Master's or PhD in computer science, mathematics, physics, or related field.
  • Experience with generative models for 3D content pipelines using applications like Houdini, Maya, or Blender.
  • Experience in 3D rendering for simulation, games, cloud computing, or VFX.

Skills

PyTorchTensorFlowPythonC++Neural Radiance FieldsNerfGaussian Splatting3D Reconstruction3D GraphicsLinear AlgebraHoudini

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