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.
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.
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