Research Intern, Platform Aware Model Optimization (PhD)
- Pittsburgh, PA
Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.
The Facebook Reality Labs (FRL) 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. Our team in FRL Pittsburgh research group is looking for exceptional interns to help us explore hardware aware model optimization to pave the way for deploying real-time and low latency telepresence in virtual reality where you can be with anyone, anywhere, at anytime. Our work covers both short term verification with off-the-shelf SoC platform and long term research on custom accelerators. In our intern project, you will dive deeply into software and hardware codesign for model optimization. If you have expertise in neural network quantization and architecture optimization with a solid background in computer architecture and machine learning, we expect you will find the work here highly intriguing.Come join us as we make photorealistic telepresence in VR happen!
- Investigate real-time model optimization methods for SoC and Neural Network accelerators
- Research new quantization/compression methods for VAE based neural networks architectures
- Collaborate with team on verification of proposed methods
- Research in accelerating distributed training of VAE
- Currently has, or is in the process of obtaining, a PhD in Computer Science & Engineering, Machine Learning, Electronics, Physics, or related field
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
- Must be available for 3 month to 6 month internship between January 1, 2021 and December 31, 2021
- Interpersonal skills: cross-group and cross-culture collaboration
- Experience with model quantization/NAS
- Experience with applications of Image Processing, Computer Vision, or Computer Graphics
- Intent to return to degree-program after the completion of the internship
- 2+ years of experience of Neural Network Optimization, Computer Vision/Graphics, SoC run-time optimization, Distributed Computing, Numerical Optimization, and Pytorch
- Proven track record of achieving significant results as demonstrated by patents and first-authored publications at leading workshops or conferences such as CVPR, SIGGRAPH, NeurIPS, ICML, SysML, ICML, ICLR, DAC, or similar
- Demonstrated engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g., GitHub)
Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at email@example.com.
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