Research Intern - Machine Learning Acceleration (PhD)
Sunnyvale, CA
You will use your background in Machine Learning to enable efficient hardware acceleration of ML algorithms for Computer Vision and Image Processing in AR and VR devices. You will also have an unique opportunity to optimize production systems, as well as help future-proof our silicon and software by proactively understanding state of the art research and develop hardware or software solutions to mitigate inefficiencies. To be successful in this role, you should possess strong software development skills, familiarity with ML algorithms and framework/toolchains and hands-on experience in software and hardware co-design, especially in the context of ML.Research Intern - Machine Learning Acceleration (PhD) Responsibilities
- Collaborate with computer architects, software, ML and silicon engineers, to map and optimize ML workloads on various backend targets including CPU’s, DSP’s and Deep Learning Accelerators.
- Perform ML algorithm, software, hardware co-design to achieve best energy and performance efficiency.
- Develop performant C/C++ kernels and optimize domain specific compilers to port industry standard ML libraries to custom hardware.
- Review SOTA research trends in hardware specific ML model optimizations and mapping
- evaluate and integrate promising techniques into shipping products.
- Run analysis/profiling , identify performance and power bottlenecks on the actual h/w, virtual platforms, simulators or emulators and provide feedback for optimizations across the stack.
- Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Electrical Engineering or related field.
- Experience with Python (or similar) scripting and exposure to ML frameworks like Pytorch/TF.
- Interpersonal experience: cross-group and cross-culture collaboration.
- Experience in software design and programming in C/C++.
- Understanding of computer architecture and performance implications.
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
- Experience with h/w acceleration on GPU’s/CPU’s/DSP’s/custom-ASICs.
- Understand classic ML, CV algorithms , DeepLearning algorithms like BERT, RNN, CNN and frameworks like Tensorflow/Pytorch.
- Familiarity with the state of art ML algorithm optimizations like Neural Architecture Search, quantization, pruning etc.
- Familiarity with Deep learning compilers like tensor-rt, XLA is a plus.
- Familiarity with high performance sw kernel development for customized ISA.
- Familiarity with code profiling and debug tools. Tools in the context of ML is a plus.
- Comfortable with reading others code, tracing them, and code refactoring.
- Intent to return to degree-program after the completion of the internship.
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.
Tags: Architecture BERT Computer Science Computer Vision Deep Learning Engineering GPU Machine Learning PhD Physics Python PyTorch Research RNN TensorFlow VR
Perks/benefits: Career development Equity Flex vacation Health care Salary bonus
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