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# AI Engineer, 3D Computer Vision, Self-Driving

- **Company:** Tesla Motors
- **Location:** Palo Alto, CA, United States
- **Salary:** $176,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computing Platforms, Computer Vision, Object Detection, Computational Geometry, Sensor Fusion, Signal Processing, Software Engineering, Deep Learning, Gaussian, Build Tools
- **Published:** July 24, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/81412668/1

## About the Role

* Experience with 3D computer vision and graphics concepts such as camera models, multi view geometry, and rendering pipelines
 * Domain expertise in an area of computer vision such as object detection & tracking, pose estimation, depth estimation, panoptic segmentation, 3D reconstruction, visual SLAM, structure from motion, neural rendering (e.g. NeRFs or gaussian splatting), novel view synthesis
 * Solid mathematical fundamentals including linear algebra, computational geometry, vector calculus, probability theory, and numeric optimization
 * Understanding of modern deep learning techniques (such as transformers, diffusion models, autoregressive models, multi-modal models, CNNs, etc.)
 * Experience in real time graphics or non-real time rendering is a plus
 * Exposure to sensor fusion, signal processing, computational photography, and robotics is a plus

## Description

As a member of the Tesla AI Team, you will build systems for offline and online 3D reconstruction and scene understanding that are robust, accurate, and performant. You will work on a world class spatial computing platform deployed at scale.
What You'll Do

 * Leverage state of the art techniques for spatial computing (such as NeRFs, Diffusion Models, Gaussian Splatting, Multiview Stereo, TSDF Fusion, Structure from Motion, SLAM)
 * Improve mission critical perception systems that enhance customer comfort and safety for all Tesla cars on the road (driving autonomously or not).
 * Push the boundaries of real world AI
 * Strict adherence to strong software engineering practices to develop novel work quickly and safely


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