Evermont
Stealth Mode
How can removing sensors make the car safer?
Maybe it's because the sensor data overloads the processor and increases latency?
Somebody should invent a co-processor capable of handling the sensor data in real time and with minimal power consumption ...
PS: Just speaking with the ogre, and, in his opinion Musk's allusion to AI does not mean Akida, because if it were to be Akida, he wouldn't need to abandon the ultrasound sensors.
Recent news suggests a continued emphasis on AI utilisation for autonomy. Someone should really sell Elon the benefits on on-chip learning.
AI Integration Software Engineer, Autonomy
Job Category | Autopilot & Robotics |
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Location | PALO ALTO, California |
Req. ID | 136288 |
Job Type | Full-time |
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What to Expect
As an AI Integration Software Engineer within the Autonomy group, you will have the opportunity to apply your technical skills to foundational code targeting automation, validation, and optimization of AI workloads for Autopilot and Humanoid robot. The nature of the role is multi-disciplinary, and it means that the code you will write, debug, and maintain will contribute to deploying Neural Networks trained by Machine Learning engineers. You will be developing system tools to benchmark, characterize and optimize the latency and throughput of the AI workloads on the FSD chip. You will write tests and integrate with our evaluation pipeline to continuously validate the AI deployment flow.
What You’ll Do
- Write, debug and maintain robust software for Autopilot and Humanoid robot AI deployment stack; depending on needs and your interests/skills, you might work on code related to our Camera & Vision stack, write custom GPU kernels for AI models, or make our NN evaluation software more stable and performant.
- Automate the flow of deploying Neural Networks and reduce the time it takes for AI models to go from Pytorch land to Tesla cars.
- Optimize Tesla's in-house AI ASIC resources usage by profiling the Neural Network execution, consult with both AI scientists and hardware architects and introduce new features in the Neural Network deployment stack.
- Advocate for best coding practices amongst the group, build tools helping engineers to write better code (for instance, performance/memory tracking)
- Experience programming C/C++ including modern C/C++ (C++14/17/20), and Python.
- Experience or familiarity with Computer Vision, Machine Learning & related software concepts.
- Experience with performant software design, compiler design and/or hardcore lower-level C code.
- Experience with at least one of the following preferred: Cuda/OpenCL, SIMD, and multithreading.
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AI Inference Software Engineer, Autonomy | Tesla Careers
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