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Research Scientist Intern, Foundation Model Optimization (PhD)

Meta

Menlo Park, CAInternship$7,650–12,667/moSeen 1 day agoSeen in employer's feed 1 day 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

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Doctorate

Job overview

Meta’s Efficiency and On-Device AI team in Reality Labs seeks a Research Scientist Intern focused on language and vision model optimization. The intern will develop efficient large language and vision foundation models, research optimization for resource-constrained devices, and explore joint optimization of models and assistant systems. The role also involves personalization, model compression, novel architectures, and collaboration with research and engineering teams.

Skills & qualifications

RequiredNice to have

Skills

LLM ResearchVision Foundation Model ResearchModel OptimizationAssistant System OptimizationPersonalizationModel CompressionEfficient InferenceEfficient Model ArchitecturesMultimodal ModelingData-Centric Model TuningModel EvaluationDeep LearningTransformersPyTorchJAXPythonShell ScriptingLarge-Scale Foundation Model TrainingLLM Agents and Orchestration

Qualifications

PhD in Artificial Intelligence or Related FieldWork Authorization in Employment CountryReturn to Degree ProgramCV/NLP/ML Publications

Full job description

Summary:

Meta's mission is to give people the power to build community and bring the world closer together, and the Meta Reality Labs organization focuses on delivering this vision through AR/VR/SG devices.Meta's Efficiency and On-Device AI team within the Reality Labs organization is seeking a Research Scientist Intern with a focus on language/vision model optimization. As a Research Scientist Intern, your primary objective is to develop cutting-edge efficient LLMs and vision foundation models.

Required Skills:

Research Scientist Intern, Foundation Model Optimization (PhD) Responsibilities:

  1. Perform LLM and vision foundation model research that leads to publications in top-tier CV/NLP/ML conferences.

  2. Develop model optimization algorithms and infrastructure to enable deployment of models in resource-constrained settings, such as mobile phones and AR/VR/MR/SG devices.

  3. Research joint optimization of models and the surrounding assistant system, including planning, memory, tool use, and coordination across device and cloud.

  4. Explore personalization, model compression and efficiency, and novel model architectures including omni-modal capabilities.

  5. Collaborate with cross-disciplinary research and engineering teams.

Minimum Qualifications:

Minimum Qualifications:

  1. Currently is in the process of obtaining a PhD in the field of Artificial Intelligence or related field

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

  3. Hands-on experience in deep learning algorithms and techniques, e.g., transformers

  4. Experience with deep learning software libraries such as PyTorch/JAX

  5. Experience with scripting languages such as Python and shell scripts

Preferred Qualifications:

Preferred Qualifications:

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

  2. Experience with large scale foundation model training and on-device foundation model optimization

  3. Experience in one or more of: LLM agents and orchestration, personalization, model compression and efficient inference, efficient model architectures, multi-modal modeling, data-centric approaches for model tuning and evaluation

  4. Proven track record of publications at CV/NLP/ML conferences/journals such as NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, AAAI, ACL, EMNLP

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].

How this job compares

Set against the 2,289 open Research Scientist jobs on Olive Jobs, counted October 29, 2026.

Pay
  • This posting$7,650–12,667/mo
  • California median$180–270K/yr495 salary ranges
  • US median$34–48/hr45 hourly ranges
Openings
Olive Jobs lists 713 open Research Scientist jobs in California and 2,289 across the US. 3% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
Research Scientist postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 2 to 6 years (1,264 postings).
Education
This posting asks for a doctorate or professional degree; 821 of the 2,289 open Research Scientist jobs (36%) ask for a doctorate or professional degree.

Counted across the open, public US postings on Olive Jobs on October 29, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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