Machine Learning Hardware Research Scientist
About The Position
Reality Labs focuses on delivering Meta's roadmap through creating advanced AI enabled wearables. The compute performance and power efficiency requirements of wearables require custom silicon. Reality Labs Silicon team is driving the state-of-the-art forward with breakthrough work in AI, augmented reality, computer vision, machine learning, graphics, displays, and sensors. Our chips will enable wearable devices where our real and virtual world will mix and match throughout the day. We are growing our team and are seeking engineers who will work with a group of individuals using your skills to implement and contribute to the development and optimization of accelerators for emerging technologies and applications.
Requirements
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
- PhD in Electrical Engineering or Computer Science or equivalent work experience
- Experience in digital design, microarchitecture, or performance modelling
- Experience with computer architecture, including CPU and CV/ML accelerators
- Experience with Machine learning models, algorithms or accelerator architecture
- Experience with at least 1 procedural programming language (C, C++, Python etc)
Nice To Haves
- Experience in ASIC design flow (Design, Verification, Synthesis)
- Experience with TensorFlow / Pytorch or similar machine learning toolsets
- Familiarity with the state-of-art-ML algorithm optimizations like Neural Architecture Search, quantization, pruning etc
Responsibilities
- Identify and solve multi-discipline ML acceleration problems involving algorithms, network design, hardware architecture and wearable use cases
- Work across hardware and software, to solve co-design problems with other research scientists working in this area
- Assist with performance/power analysis of machine learning models
- Algorithmic modeling of machine learning workloads
- Develop tooling and methodologies for efficient design of ML accelerators
Benefits
- $122,000/year to $181,000/year + bonus + equity + benefits
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
