Research Scientist Intern, Core AI - Language (PhD)

The Core AI group at Reality Labs Research is seeking an outstanding Research Scientist Intern for 2026 to advance the science and engineering of large‑scale LLM training, efficient LLM algorithms, small LLMs, reasoning capabilities, and pre‑/post‑training methods. As an intern, you will lead impactful research projects and develop reproducible training and evaluation pipelines in a top‑tier industrial research environment.

Your research project includes but not is limited to:
- Large‑scale LLM training and data curation
- Efficient LLM algorithms
- Small LLMs (design, training, deployment)
- LLM reasoning and agents

Our internships are twelve (12) to twenty four (24) weeks long and we have flexible start dates in 2026.Research Scientist Intern, Core AI - Language (PhD) Responsibilities

• Plan and execute ambitious research to advance LLM pre-training and post‑training (reasoning, alignment, efficiency, and compact model design).
• Build scalable pipelines for data curation, training, and evaluation
• run rigorous ablations and analyses to generate actionable insights.
• Develop reproducible experimentation and contribute high‑quality code, documentation, and research communications.
• Publish and present research findings to internal and external audiences
• collaborate across research, engineering, and product teams.

Minimum Qualifications

• Strong programming skills in Python and experience with modern deep learning frameworks (e.g., PyTorch)
• Research and/or work experience in at least one of the following: 1) Large‑scale LLM pre-training/post-training, data curation, 2) Efficient LLM algorithms, 3) Small model architecture and training, 4) LLM reasoning or post‑training (instruction tuning/reinforcement learning), 5) LLM agent systems (tool‑use, planning, multi‑step workflows, evaluation)
• Demonstrated research impact (e.g., publications, patents, open‑source contributions, awards/fellowships), as well as publications at leading conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred Qualifications

• Experience with distributed training and large‑scale experimentation
• Experience with efficiency techniques (e.g., quantization or distillation) and/or long‑context optimizations
• Experience building systems based on machine learning, reinforcement learning and/or deep learning methods
• Demonstrated SWE or research experience via internships, competitive benchmarks, open‑source tools, or widely used libraries

For those who live in or expect to work from California if hired for this position, please click here for additional information. About Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
$7,650/month to $12,134/month + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.



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