Research Scientist - Reality Labs

Meta Meta · Big Tech · New York, NY

Research Scientist at Meta Reality Labs focusing on developing and optimizing LLMs for AI-powered neuromotor interactions in wearable devices. The role involves leading research, setting technical direction, and transitioning LLM research into production on constrained hardware, with a focus on knowledge distillation and on-device optimization.

What you'd actually do

  1. Lead the design, development, and optimization of Large Language Models for wearable device applications
  2. Set technical direction for LLM-related research projects involving 3-4 researchers and engineers
  3. Conduct research and experiments to improve language model accuracy, efficiency, and on-device performance
  4. Collaborate with cross-functional teams (engineering, HCI, product) to transition LLM research into production
  5. Explore and adopt novel model optimization, quantization, and efficiency techniques for resource-constrained environments

Skills

Required

  • PhD in Computer Science, Machine Learning, Natural Language Processing, or a related technical field
  • Expertise in Large Language Models — including architecture design, training, fine-tuning, and/or deployment
  • Programming experience in Python
  • Hands-on experience with deep learning frameworks such as PyTorch
  • Experience developing machine learning models at scale from inception to impact
  • Proven track record of architecting knowledge distillation (KD) pipelines to compress frontier LLMs into optimized edge models
  • Experience bringing LLM-based products from research to research
  • Demonstrated software engineering experience
  • Technical leadership experience setting direction for a team of 3-4 researchers/engineers
  • First-authored publications at peer-reviewed AI/NLP conferences
  • Experience with on-device or edge language model optimization (quantization, sparsity, distillation, knowledge distillation)
  • Deep expertise in logit matching, task-specific SFT data synthesis, and instruction-tuning sub-billion models for production tasks

Nice to have

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

What the JD emphasized

  • Proven track record of architecting knowledge distillation (KD) pipelines to compress frontier LLMs into optimized edge models
  • Experience bringing LLM-based products from research to production
  • First-authored publications at peer-reviewed AI/NLP conferences (e.g., ACL, EMNLP, NeurIPS, ICML, ICLR, NAACL)
  • Experience with on-device or edge language model optimization (quantization, sparsity, distillation, knowledge distillation)

Other signals

  • LLM research
  • on-device optimization
  • wearable devices
  • neuromotor interactions