Research Intern
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Job Description
About Cohere
Cohere’s mission is to scale intelligence to serve humanity. They are focused on training and deploying frontier models for developers and enterprises, enabling them to build AI systems for content generation, semantic search, RAG, and agents. The company values hard work, speed, and prioritizing customer needs. Cohere is a team of researchers, engineers, and designers passionate about their craft and believes in the importance of diverse perspectives.
Job Description: Research Intern
This Research Internship offers the opportunity to collaborate with Cohere researchers and tools to design and implement novel research ideas and ship state-of-the-art models to production. There are openings in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning. Cohere is open to intern applications in any research area relating to LLMs to broaden your research connections while obtaining deep experience in a growing AI startup.
Key Responsibilities:
• Conducting cutting-edge machine learning research, building and training large language models.
• Focusing on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc.
• Disseminating research results through publications, datasets, and code.
• Contributing to research initiatives that have practical applications in Cohere’s product development.
Eligibility Requirements:
• Currently pursuing a PhD in Machine Learning, NLP, or a related discipline.
• Available for a full-time internship lasting 4-6 months.
• Eligible for work authorization in the country of employment.
You May Be a Good Fit If You Have:
• Experience using large-scale distributed training strategies, data annotation and evaluation pipelines, or implementing state of the art ML models.
• Familiarity with autoregressive sequence models, such as Transformers.
• Strong communication and problem-solving skills.
• Knowledge of programming languages such as Python, C, C++, Lua.
• Knowledge of ML frameworks such as JAX, Pytorch and Tensorflow.
• Previous experience in building systems based on machine learning and deep learning techniques.
• Passion for applied NLP models and products.
Preferred Qualifications:
• Demonstrated expertise through publications in top-tier venues.
• Proven ability to tackle analytical problems using quantitative methodologies.
• Proficiency in handling and analysing complex, high-dimensional data.
• Experience in applying theoretical and empirical research to real-world problem-solving.
