Research Scientist Intern, Machine Learning Acceleration (PhD)

About the position

The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of AR and VR, which together will become as universal and essential as smartphones and personal computers are today. The focus of our team is on computer graphics and displays with primary research on the efficient synthesis of high-quality images for AR/VR systems. Our current research areas include custom graphics hardware, rendering algorithms for AR/VR, such as ray casting and neural rendering, perceptual aware rendering, neural compression, and generative AI for 3D graphics. 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 a 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.

Responsibilities

• Enable efficient hardware acceleration of ML algorithms for Computer Vision and Image Processing in AR and VR devices.
• Optimize production systems for AR/VR applications.
• Develop hardware or software solutions to mitigate inefficiencies in silicon and software.
• Understand state of the art research in ML and apply it to current projects.

Requirements

• 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.
• 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.
• Intent to return to a degree-program after the completion of the internship.
• Experience with hardware acceleration on GPU's/CPU's/DSP's/custom-ASICs.
• Proven track record of achieving significant results, as demonstrated by first-authored publications at leading workshops or conferences in computer vision/machine learning (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML) or computer architecture (e.g., ISCA, ASPLOS, MICRO, HPCA).
• Experience and understanding of 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.

Nice-to-haves

• Familiarity with tools in the context of ML is a plus.
• Ability to read code, trace them, and code refactor.