Research Scientist - Reality Labs

Meta; Indianapolis (IN); On-site; USD 184,000 - 257,000; Full time

Job summary

Meta Reality Labs is seeking a Research Scientist to advance large language models for wearable devices. The role focuses on design, optimization, and deployment of LLMs with on-device efficiency, in a cross-functional setting with engineering, HCI, and product teams.

You will guide 3–4 researchers and engineers, and drive research-to-production translation for constrained hardware. The ideal candidate has extensive LLM expertise, Python and PyTorch proficiency, and a track record of autonomous

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field.
• PhD in CS/ML/NLP (completed before joining Meta).
• Expertise in Large Language Models — architecture, training, fine-tuning, or deployment.
• Python programming and PyTorch experience.
• Experience building ML models at scale from inception to impact.
• 5+ years of autonomous ML/NLP research experience.

Responsibilities

• Lead the design, development, and optimization of Large Language Models for wearable device applications.
• Set technical direction for LLM 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 to transition LLM research into production.
• Explore and adopt model optimization techniques for resource-constrained environments.
• Stay current with state-of-the-art advances in LLMs, NLP, and related fields.

Job description

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

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
6. Stay current with state-of-the-art advances in LLMs, NLP, and related fields

Minimum Qualifications

1. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
2. 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
3. Demonstrated expertise in Large Language Models — including architecture design, training, fine-tuning, and/or deployment
4. Programming experience in Python and hands-on experience with deep learning frameworks such as PyTorch
5. Experience developing machine learning models at scale from inception to impact
6. 5+ years of research experience working autonomously on ML/NLP problems

Preferred Qualifications

1. Proven track record of architecting knowledge distillation (KD) pipelines to compress frontier LLMs into optimized edge models
2. Experience bringing LLM-based products from research to production
3. Demonstrated software engineering experience via internship, work experience, or widely used contributions in open source repositories
4. Technical leadership experience setting direction for a team of 3-4 researchers/engineers
5. First-authored publications at peer-reviewed AI/NLP conferences (e.g., ACL, EMNLP, NeurIPS, ICML, ICLR, NAACL)
6. Experience with on-device or edge language model optimization (quantization, sparsity, distillation, knowledge distillation)
7. 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 [e-mail].