[Skip to main content](#main-content)

[ OpenNash ](https://opennash.com/) / [Jobs](https://jobs.opennash.com/) [ 01 Search jobs](https://jobs.opennash.com/search/)[ 02 Companies](https://jobs.opennash.com/explore/)[ 03 Hiring report](https://jobs.opennash.com/reports/hiring/)[ 04 AI assistants](https://jobs.opennash.com/connect/)[ 05 How it works](https://jobs.opennash.com/methodology/)

Meta Platforms · Menlo Park, CA

# Research Scientist Intern, PhD — Meta Superintelligence Labs

Menlo Park, CA Early career Research & Science 

Listed on Meta Platforms’s official careers site. Listed as of November 1, 2026. Check that it is still open and apply there.
[Apply on Meta Platforms’s careers site →](https://www.metacareers.com/jobs/1510576574212840/)

[OpenNash Jobs](https://jobs.opennash.com/) / [Meta Platforms](https://jobs.opennash.com/companies/meta-platforms/) / Research Scientist Intern, PhD — Meta Superintelligence Labs

## Job description

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization. Meta is seeking Research Interns to join our AI Search research team.

We are committed to advancing the field of artificial intelligence by making fundamental advances in how AI agents learn from their own experience — improving their search and reasoning workflows, retaining useful knowledge, and transferring those gains to unfamiliar tasks. A central research challenge is making repeated self-improvement reliable when feedback is sparse or noisy. The intern will work in one of three directions, scoped closer to the start date together with the intern manager:
- Learning to improve research workflows — agents learn better search, tool-use and verification strategies from prior attempts by improving their harness: the workflow, memory, tools and feedback loop around the model. Topics include meta-learning across tasks, automated agent design, and learning from natural-language feedback.
- Persistent memory and continual learning — agents retain useful lessons and update knowledge across tasks, whether in context, in compressed memory, or in weights, without forgetting what they already know. Topics include long-context modeling, context compression, continual learning, and test-time training.
- Learning from imperfect feedback — turning noisy judgments and failed attempts into useful learning signals, and improving the strategy an agent uses to learn, including how it selects and evaluates its next improvement.

Topics include reward learning, credit assignment, and learning to learn. Across all three directions, the key test is whether improvements transfer to new tasks. The goal is to develop novel methods and experiments toward a first-author submission at a leading ML/NLP venue. Recent internships on this team have produced work such as REFRAG, a new architecture for retrieval-augmented generation.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

## Responsibilities

Develop novel state-of-the-art methods for self-improving, agentic AI systems, leveraging a range of deep learning and reinforcement learning techniques. Design and run experiments that test whether agent improvements generalize and transfer to unseen tasks. Perform research to advance the science and technology of intelligent machines. Help analyze and improve the reliability and robustness of the resulting methods. Collaborate with researchers and cross-functional partners, including communicating research plans, progress, and results.

Disseminate and publish research results, and contribute to research that can be applied to Meta product development.

## Qualifications

Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a relevant technical field
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Research experience in machine learning, deep learning, and/or natural language processing Experience with Python Experience with deep learning frameworks such as PyTorch or TensorFlow Intent to return to the degree program after the completion of the internship/co-op
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, or first-authored publications at leading workshops or conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP, or COLM Research experience in large language models, foundation models, or post-training Experience with agentic systems: agent workflows, tool use, agentic search, or retrieval-augmented generation (RAG) Experience with reinforcement learning, reward modeling, or credit assignment Experience with continual/lifelong learning, meta-learning, or test-time training Experience with long-context modeling, memory, context compression, or efficient inference Experience with LLM evaluation and setting up ML experiments and analyzing their results Experience with Hugging Face Transformers, and training or fine-tuning transformer models Experience with distributed training Experience working and communicating cross functionally in a team environment
- Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g.

GitHub)

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 25, 2026
- Last checked: Nov 1, 2026
- Listed for: 7 days
- Location: Menlo Park, CA[Apply on Meta Platforms’s careers site →](https://www.metacareers.com/jobs/1510576574212840/)

## Hiring at Meta Platforms
- Open jobs: 1,310
- New in the last 7 days: After two weekly collections
- Tracked since: Jul 11, 2026

[All Meta Platforms jobs](https://jobs.opennash.com/companies/meta-platforms/) · [Weekly hiring report](/reports/hiring/)

## More jobs at Meta Platforms

### [AI Research Engineer](https://jobs.opennash.com/companies/meta-platforms/jobs/2ce2068cd9fcf1053dc1/)

Menlo Park, CA

### [AI Research Manager - Meta Superintelligence Labs](https://jobs.opennash.com/companies/meta-platforms/jobs/2b9038fb99fde6a938ed/)

Menlo Park, CA

### [AI Research Scientist - FAIR, MSL](https://jobs.opennash.com/companies/meta-platforms/jobs/bb3308d76ff6faee2fc3/)

Menlo Park, CA

### [AI Research Scientist - MSL FAIR Foundations](https://jobs.opennash.com/companies/meta-platforms/jobs/d18ce9293309ea34ebd4/)

Menlo Park, CA

### [AI Research Scientist, AI Safety and Security](https://jobs.opennash.com/companies/meta-platforms/jobs/c4a620c30eddb9df62ec/)

Menlo Park, CA

## Similar jobs at other companies

### [Research Scientist, Autonomous Systems and Physical AI Research - PhD New College Grad 2026](https://jobs.opennash.com/companies/nvidia/jobs/49e1ed00a765e733c04f/)

NVIDIA · US, CA, Santa Clara

### [Research Scientist, Robotics Research - PhD New College Grad 2026](https://jobs.opennash.com/companies/nvidia/jobs/697d6dacb02ae2cbd232/)

NVIDIA · US, WA, Seattle

### [Sr Director, Translational Research Scientist - MD/PhD](https://jobs.opennash.com/companies/intuitive/jobs/dced5924d3d9b26da62d/)

Intuitive · Sunnyvale, CA, United States

### [Staff Research Scientist, Intern - PhD Agentic AI](https://jobs.opennash.com/companies/visa/jobs/5b9cf35a21f3dfab9a32/)

Visa · Austin, US, TX

### [Staff Research Scientist, Intern - PhD Quantum](https://jobs.opennash.com/companies/visa/jobs/4ef02a9b7b772b793358/)

Visa · Foster City, US, CA

OpenNash lists jobs from employers’ own careers sites and does not handle applications.
Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

[ OpenNash ](https://opennash.com/)

AI-native services firm that builds custom software and 24/7 AI agents.

OpenNash Jobs is an OpenNash Applied AI project.
[Book time with OpenNash](https://calendly.com/opennash/new-meeting?hide_gdpr_banner=1)

Jobs
- [Search jobs](https://jobs.opennash.com/search/)
- [Companies](https://jobs.opennash.com/explore/)
- [Hiring report](https://jobs.opennash.com/reports/hiring/)
- [AI assistants](https://jobs.opennash.com/connect/)
- [How it works](https://jobs.opennash.com/methodology/)

OpenNash
- [opennash.com](https://opennash.com/)
- [Services](https://opennash.com/ai-agent-consulting/)
- [OpenNash CX](https://opennash.com/cx/)
- [AI Tools](https://opennash.com/ai-tools/)
- [Blog](https://opennash.com/blog/)
- [About](https://opennash.com/about/)

Contact
- [hello@opennash.com](mailto:hello@opennash.com)

- [LinkedIn](https://www.linkedin.com/company/opennash)

- [Support](https://jobs.opennash.com/support/)

- [Privacy](https://jobs.opennash.com/privacy/)

- [Terms](https://jobs.opennash.com/terms/)

© 2026 OpenNash, Inc. Company names and public job postings belong to their respective owners. Employers control source availability and application decisions.