Meta's Reality Labs (RL) is searching for a Research Scientist to join their Research & Development teams. This role will focus on developing innovative solutions for efficient training and on-device inference of vision and language models for AR, VR, and edge devices. Responsibilities include identifying and resolving multi-disciplinary ML acceleration problems, working across hardware and software to solve co-design challenges, inventing novel ML accelerator and system architecture solutions, developing model compression and scalability techniques, optimizing models on hardware accelerators, influencing partners, defining use cases, evaluating different approaches, and staying updated with the latest research advancements in ML acceleration.
Good To Have:- Experience or knowledge of training/inference of Large scale AI models - CV and/or LLMs
- Experience or knowledge of architecting ML hardware accelerators and systems
- Experience or knowledge of on-device algorithm development including hardware-aware ML models and/or optimizing ML compilers for efficient deployment on AI accelerators
- Experience with PyTorch, TensorFlow or similar machine learning toolsets
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as ICLR, NeurIPS, CVPR, ACL, ICML, MLSys, ISCA, MICRO, DAC, ASPLOS etc.
- Demonstrated research and engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
- Experience working and communicating cross functionally in a team environment
- Experience solving complex problems and comparing alternative solutions, trade offs, and diverse points of view to determine a path forward
Must Have:- Bachelor's degree in CS, CE, or related field
- PhD in EE, CS, or equivalent experience
- 2+ years of experience in ML/DL domains: Model compression, hardware aware model optimizations, hardware accelerators architecture, GPU architecture, machine learning compilers, or ML systems
- Experience developing AI-System infrastructure, AI algorithms or AI hardware acceleration in C/C++ or Python