Summary:
Reality Labs at Meta is seeking a Research Scientist with deep expertise in Large Language Models (LLMs) to advance our work in AI-powered neuromotor interactions for wearable devices. We are building next-generation language capabilities that enable natural, expressive, and intelligent communication through Meta's wearable platforms via our industry-leading electromyography (EMG) program.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.
Required Skills:
Research Scientist - Reality Labs 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
Minimum Qualifications:
Minimum Qualifications:
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
Preferred Qualifications:
Preferred Qualifications:
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
Public Compensation:
$184,000/year to $257,000/year + bonus + equity + benefits
Industry: Internet
Equal Opportunity:
Meta is proud to be an Equal Employment 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. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta 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 protected].
