Software Engineer – AI Inference Codesign
| Company | Tesla |
|---|---|
| Location | Palo Alto, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Mid Level |
Requirements
- Degree in Engineering, Computer Science or equivalent in experience and evidence of exceptional ability
- Proficiency with Python and C++, including modern C++ (14/17/20)
- Experience with AI networks, such as CNNs, transformers, and diffusion model architectures, and their performance characteristics
- Understanding of GPU, SIMD, multithreading and/or other accelerators with vectorized instructions
- Exposure to computer architecture and chip architecture/micro-architecture
- Specialized experience in one or more of the following machine learning/deep learning domains: Model compression, hardware aware model optimizations, hardware accelerators architecture, GPU/ASIC architecture, machine learning compilers, high performance computing, performance optimizations, numerics and SW/HW co-design
Responsibilities
- Research and implement state-of-the-art machine learning techniques to achieve high performance on our edge hardware
- Optimize bottlenecks in the inference flow, make precision/performance tradeoff decisions and figure out novel techniques to improve hardware utilization and throughput
- Implement/improve highly performant micro kernels for Tesla’s AI ASIC
- Work with AI teams to design edge friendly neural network architectures
- Collect extensive performance benchmarks (latency, throughput, power) and work with HW teams to shape the next generation of inference hardware, balancing performance with versatility
- Experiment with numerical methods and alternative architectures
- Collaborate with the compiler infrastructure for programmability and performance
Preferred Qualifications
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No preferred qualifications provided.