Research Scientist Intern, Large Language Models (PhD)

Meta
London
2 months ago
Applications closed

Related Jobs

View all jobs

(Only 24h Left) Data Scientist, Internship, United Kingdom -BCG X

Machine Learning Research Scientist - PhD, NLP, LLM

Senior Data Scientist (Document Search)

Senior Data Scientist (Document Search)

Principal Data Scientist - NLP

Principal Data Scientist – Operational Research, Simulation & ML

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

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.