Job description
What to Expect
What You’ll Bring
As part of the Tesla Autopilot team, you will help lead the development of photorealistic, procedural environments that test, challenge and improve our Full Self Driving technology. Work alongside other artists, technical artists and simulation engineers to grow coverage of our virtual world to include more regions, variations, biomes and drivable topologies.
Your goal will be to supercharge the synthetic datasets that our perception neural networks train on, support our planning controls teams by convincing the car it is driving in real locations, and ensure the safety of our products by reproducing real driving behavior.
What You’ll Do
Your goal will be to supercharge the synthetic datasets that our perception neural networks train on, support our planning controls teams by convincing the car it is driving in real locations, and ensure the safety of our products by reproducing real driving behavior.
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Use Houdini, Maya and in-house tools to create large, detailed road networks and associated assets in a procedural manner
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Respond to training dataset requirements and Full Self Driving product direction by providing realistic environments and asset
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Work closely with the AP Simulation team to continuously improve content realism and asset creation workflows
- Proven experience in AAA gaming or similar industry with track record of high-quality shipped products
- Background and experience creating procedural content
- Excellent knowledge of Houdini & Vex
- Confident with Python
- Robust experience 3D production pipelines as used in game development
- Understanding of graphics pipeline and how to design and deliver high performance assets
- Proactive and able to tackle novel problems with a first-principles approach
- Solid spatial math skills related to computing road and driving geometry
Plus:
- Unreal Engine 5.0x experience with tool and utility building in Blueprints and other scripting languages
- Experience with Git and Linux as well as other version control
- Understanding of vision-based ML and experience with NN training
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