Machine Learning Engineer - 3D Sensor Simulation
Zoox
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- Pay
- $189K to $283K
- a year
- Location
- Foster City, CA
- Work style
- Hybrid
- Job type
- Full time
- Posted
- Oct 12
- 7 days ago
Career path
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About the company
Zoox
Automotive · 1,001 to 5,000 employees
What you'll do
- Improve the realism of simulated LiDAR, radar, and camera sensors.
- Enable the robotics autonomy stack to learn and improve through in-the-loop simulation and high-fidelity synthetic data.
What you need
- 3+ 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
- 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
Key skills
machine learningsensor dataLiDARradarcameras3D simulationlearned sensor modelsneural 3D reconstruction
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Read the full posting here
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 humans.