Research Scientist - Reality Labs

Our team within the Wearables Input and Interaction organization is multi-disciplinary, combining machine learning, language modeling, and on-device optimization to push the boundaries of what's possible with language AI on constrained hardware. This is a unique opportunity to conduct cutting-edge LLM research with direct product impact - shaping how people interact with the next generation of wearable devices.

We are looking for a researcher who can drive innovation in language model development, optimization, and deployment while setting technical direction for a small team. If you are passionate about building state-of-the-art language models and translating research into real-world products, we want to hear from you.

Responsibilities

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

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Currently has, or is in the process of obtaining, a PhD in Computer Science, Machine Learning, Natural Language Processing, or a related technical field. Degree must be completed prior to joining Meta Demonstrated expertise in Large Language Models - including architecture design, training, fine-tuning, and/or deployment Programming experience in Python and hands-on experience with deep learning frameworks such as PyTorch Experience developing machine learning models at scale from inception to impact 5+ years of research experience working autonomously on ML/NLP problems 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 Demonstrated software engineering experience via internship, work experience, or widely used contributions in open source repositories Technical leadership experience setting direction for a team of 3-4 researchers/engineers 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) Deep expertise in logit matching, task-specific SFT data synthesis, and instruction-tuning sub-billion models for production tasks