Research Internship Reinforcement Learning (Summer)

CohereCohere·Remote(Paris)
AI & Machine Learning
Excel

WFA Digital Insight

In a market where AI adoption is on the rise, with over 61% of companies increasing their AI investments, the demand for specialists in reinforcement learning and large language models is skyrocketing. Cohere, a pioneer in scaling intelligence, offers a unique research internship that bridges theoretical modeling with practical implementation. This role is particularly interesting for those eager to contribute to cutting-edge projects that advance the state-of-the-art in LLM training and deployment. With the global AI market expected to reach

90 billion by 2025, this internship provides invaluable experience for candidates looking to make a mark in the industry. Before applying, candidates should be aware that a strong background in machine learning, particularly reinforcement learning and deep learning, is essential, along with proficiency in Python and experience with ML frameworks.

Job Description

About the Role

The Research Internship at Cohere is a unique opportunity for individuals to contribute to the forefront of research in reinforcement learning and large language models. This internship is part of Cohere's mission to scale intelligence to serve humanity, focusing on training and deploying frontier models for developers and enterprises. The role entails working on two interconnected projects: combining self-distillation and reinforcement learning for LLMs and dealing with extremely large rollouts in RLVR. The successful candidate will be part of a team of researchers, engineers, designers, and more, who are passionate about their craft and committed to excellence.

As part of this team, the intern will be responsible for conducting literature reviews, implementing state-of-the-art algorithms, designing and executing experiments, and collaborating with researchers to analyze results. The ideal candidate should be currently pursuing a Master’s or PhD in Computer Science, Machine Learning, or a related field, with a strong background in machine learning, particularly reinforcement learning and deep learning.

The team at Cohere values diversity and celebrates different perspectives, believing that this is crucial for building great products. This internship offers a minimum duration of 4 months, starting in summer 2026, with the potential for extension. It is an excellent opportunity for those looking to advance their skills, contribute to groundbreaking research, and be part of a dynamic team.

What You Will Do

  • Conduct literature reviews to understand the current state of reinforcement learning and large language models.
  • Implement state-of-the-art algorithms in RL and self-distillation to improve LLMs.
  • Design and execute experiments to evaluate the effectiveness of proposed methods on code generation and agentic tasks.
  • Develop and maintain codebases for both theoretical modeling and practical implementations.
  • Collaborate with researchers to analyze results, refine methodologies, and prepare findings for publication.
  • Contribute to the design of mechanisms for handling large rollouts, such as summarization and hierarchical sub-agents.
  • Document progress, methodologies, and outcomes clearly and comprehensively.
  • Participate in team meetings and discussions to share insights and learn from others.
  • Apply machine learning and deep learning skills to real-world problems.
  • Stay updated with the latest developments in reinforcement learning and large language models.

What We Are Looking For

  • Strong background in machine learning, particularly reinforcement learning and deep learning.
  • Proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
  • Familiarity with LLMs and their training paradigms.
  • Experience with coding tasks, unit testing, or compiler tools is a plus.
  • Currently pursuing a Master’s or PhD in Computer Science, Machine Learning, or a related field.
  • Ability to work independently and manage complex projects.
  • Strong problem-solving and analytical skills.
  • Excellent communication skills for collaborating with a research team.
  • Prior experience with RLVR, self-distillation, or large-scale ML experiments is highly desirable.

Nice to Have

  • Experience with cloud computing platforms.
  • Knowledge of containerization using Docker.
  • Familiarity with Agile development methodologies.
  • Participation in open-source projects or personal projects related to AI.

Benefits and Perks

  • Opportunity to work on cutting-edge projects in AI.
  • Collaborative and dynamic work environment.
  • Professional development opportunities.
  • Access to the latest tools and technologies in machine learning.
  • Flexible working hours and remote work options.
  • Health insurance and retirement plans.
  • Paid time off and holidays.
  • Opportunities for networking and attending conferences.

How to Stand Out

  • Ensure you have a strong foundation in machine learning, particularly reinforcement learning and deep learning, before applying.
  • Familiarize yourself with Python and ML frameworks such as PyTorch or TensorFlow.
  • Highlight any experience with large language models and their training paradigms in your application.
  • Showcase your ability to work independently on complex projects and collaborate with a team.
  • Prepare to discuss your research interests and how they align with Cohere’s mission during the interview process.
  • Be prepared to provide examples of your problem-solving skills and analytical thinking.
  • Consider including links to personal projects or contributions to open-source projects related to AI in your application.

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