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Summary:

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 agentsOur internships are twelve (12) to twenty four (24) weeks long and we have flexible start dates in 2026.

Required Skills:

Research Scientist Intern, Core AI - Language (PhD) Responsibilities:

1. Plan and execute ambitious research to advance LLM pre-training and post‑training (reasoning, alignment, efficiency, and compact model design).

2. Build scalable pipelines for data curation, training, and evaluation

3. run rigorous ablations and analyses to generate actionable insights.

4. Develop reproducible experimentation and contribute high‑quality code, documentation, and research communications.

5. Publish and present research findings to internal and external audiences

6. collaborate across research, engineering, and product teams.

Minimum Qualifications:

Minimum Qualifications:

7. Strong programming skills in Python and experience with modern deep learning frameworks (e.g., PyTorch)

8. 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)

9. 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

10. Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred Qualifications:

Preferred Qualifications:

11. Experience with distributed training and large‑scale experimentation

12. Experience with efficiency techniques (e.g., quantization or distillation) and/or long‑context optimizations

13. Experience building systems based on machine learning, reinforcement learning and/or deep learning methods

14. Demonstrated SWE or research experience via internships, competitive benchmarks, open‑source tools, or widely used libraries

Public Compensation:

$7,650/month to $12,134/month + 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].