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Combine multiple data sources, including video, audio, thermal, mechanical, weather, and other sensors to develop and train end-to-end models for control of all vehicle accessories required for autonomous operation
Define data collection and annotation strategies for training and evaluation
Integrate directly with vehicle firmware and ship production quality, safety-critical software to the entirety of Tesla's vehicle fleet
Iterate on new features through simulation, validation, and fleet data analysis
Proficiency in writing production quality code in Python, and experience with any major deep learning framework
Proficiency in modern C++ to integrate with vehicle firmware and take projects from ideas to shipped products
An "under the hood" knowledge of deep learning modern architectures, optimization, model alignment, etc
Ability to think “out-of-the-box" to push performance beyond apparent limitations
Excellent problem-solving, critical thinking, and communication skills
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