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 who are building AI systems. The company values hard work, fast movement, and a customer-centric approach. Cohere is comprised of researchers, engineers, and designers who are passionate about their work and strive to be the best in their fields. They believe in the importance of diverse perspectives in building great products.
Job Description: Research Intern
This Research Internship offers the opportunity to collaborate with Cohere researchers and contribute to the design and implementation of novel research ideas, with the aim of shipping state-of-the-art models to production. Openings are available in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning, among others. The company is open to receiving intern applications in any research area relating to LLMs to broaden your research connections while obtaining deep experience in a growing AI startup.
Responsibilities:
• Conduct cutting-edge machine learning research, building and training large language models.
• Focus on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc.
• Disseminate research results through publications, datasets, and code.
• Contribute to research initiatives that have practical applications in Cohere’s product development.
Eligibility Requirements:
• Must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. Exceptional non-PhD candidates will also be considered.
• Must be eligible for work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout the internship period.
• Must be available for a full-time internship lasting 4-6 months.
Ideal Candidate Profile:
• 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.
• Proficiency in programming languages such as Python, C, C++, Lua, or related languages.
• 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 in relevant fields.
• Proven ability to tackle analytical problems using quantitative methodologies.
• Proficiency in handling and analyzing complex, high-dimensional data.
• Experience in applying theoretical and empirical research to real-world problem-solving.
