Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Research Scientist Intern, Large Language Models (PhD)

Meta
London
7 months ago
Applications closed

Related Jobs

View all jobs

2026 Data Scientist Internship, Amazon University Talent Acquisition

Data Science Apprentice

Research Scientist Manager, Computer Vision & GenAI

Research Scientist (Quantum Chemistry and Machine Learning), London London

Research Scientist (Quantum Chemistry and Machine Learning), London

Research Scientist (Machine Learning)

Research Scientist Intern, Large Language Models (PhD)

We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.

Responsibilities

  1. Perform research to advance the science and technology of intelligent machines.
  2. Develop novel and accurate NLP algorithms and systems, leveraging Deep Learning and Machine Learning on big data resources.
  3. Analyze and improve efficiency, scalability, and stability of various deployed systems.
  4. Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
  5. Publish research results and contribute to research that can be applied to Meta product development.

Minimum Qualifications

  1. Currently has or is in the process of obtaining a PhD degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, or 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. Experience with Python, C++, C, Java or other related languages.
  4. Experience with deep learning frameworks such as Pytorch or Tensorflow.
  5. Experience building systems based on machine learning, deep learning methods, or natural language processing.

Preferred Qualifications

  1. Intent to return to a degree program after the completion of the internship/co-op.
  2. Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICLR, ICML, ACL, NAACL, EMNLP, or similar.
  3. Experience with ML areas such as Natural Language Processing, Speech, Multimodal Reasoning & Retrieval.
  4. Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
  5. Experience with training deep neural networks for key NLP tasks.
  6. Experience with interpreting deep neural networks mechanistically, correlating their observable behavior with properties of model parameters and activations.
  7. Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
  8. Experience working and communicating cross functionally in a team environment.

Locations

Data Center

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.

Equal Employment Opportunity and Affirmative Action

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, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.

Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need support, please reach out to .

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.