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Research Scientist Intern, PhD — Meta Superintelligence Labs

Meta

Menlo Park, CAInternship$7,650–12,667/moSeen 4 days agoSeen in employer's feed 2 days ago

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At a glance

Compensation
$7,650–12,667/mo
Location
Menlo Park, CA
Role Type
Internship
Schedule
Internship
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Doctorate

Job overview

Meta seeks a PhD Research Scientist Intern for its AI Search research team, advancing methods that help AI agents learn from experience, improve search and reasoning, retain knowledge, and transfer gains to unfamiliar tasks. The intern will pursue one of three research directions, scoped with the manager near the start date, and develop methods and experiments toward a first-author submission at a leading ML/NLP venue.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningDeep LearningNatural Language ProcessingPythonPyTorchTensorFlowLarge Language ModelsFoundation ModelsPost-TrainingAgentic SystemsAgent WorkflowsTool UseAgentic SearchRetrieval-Augmented GenerationReinforcement LearningReward ModelingCredit AssignmentContinual LearningLifelong LearningMeta-LearningTest-Time TrainingLong-Context ModelingMemoryContext CompressionEfficient InferenceLLM EvaluationML ExperimentationHugging Face TransformersTransformer TrainingTransformer Fine-TuningDistributed TrainingCross-Functional CommunicationSoftware Engineering

Qualifications

PhD in Relevant Technical FieldResearch ExperienceReturn to Degree ProgramGrants, Fellowships, Patents, or PublicationsSoftware Engineering Experience

Full job description

Summary:

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.

Required Skills:

Research Scientist Intern, PhD — Meta Superintelligence Labs Responsibilities:

  1. Develop novel state-of-the-art methods for self-improving, agentic AI systems, leveraging a range of deep learning and reinforcement learning techniques.

  2. Design and run experiments that test whether agent improvements generalize and transfer to unseen tasks.

  3. Perform research to advance the science and technology of intelligent machines.

  4. Help analyze and improve the reliability and robustness of the resulting methods.

  5. Collaborate with researchers and cross-functional partners, including communicating research plans, progress, and results.

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

Minimum Qualifications:

Minimum Qualifications:

  1. 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

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

  3. Research experience in machine learning, deep learning, and/or natural language processing

  4. Experience with Python

  5. Experience with deep learning frameworks such as PyTorch or TensorFlow

Preferred Qualifications:

Preferred Qualifications:

  1. Intent to return to the degree program after the completion of the internship/co-op

  2. 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

  3. Research experience in large language models, foundation models, or post-training

  4. Experience with agentic systems: agent workflows, tool use, agentic search, or retrieval-augmented generation (RAG)

  5. Experience with reinforcement learning, reward modeling, or credit assignment

  6. Experience with continual/lifelong learning, meta-learning, or test-time training

  7. Experience with long-context modeling, memory, context compression, or efficient inference

  8. Experience with LLM evaluation and setting up ML experiments and analyzing their results

  9. Experience with Hugging Face Transformers, and training or fine-tuning transformer models

  10. Experience with distributed training

  11. Experience working and communicating cross functionally in a team environment

  12. Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)

Public Compensation:

$7,650/month to $12,667/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].

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