11 days ago

Research Internship

Cohere

On Site
Full Time
CA$90,000
Toronto, ON

Job Overview

Job TitleResearch Internship
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered SalaryCA$90,000
LocationToronto, ON

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Job Description

Who are we?

Our mission at Cohere is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future!

Why this Research Internship role?

This Research Internship offers the opportunity to collaborate with Cohere researchers and tools on designing and implementing novel research ideas and shipping state-of-the-art models to production. We have openings in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning, to name a few; and we are 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.

Please Note: To be eligible for a Research Internship, you must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. You need to be available for a full-time internship that lasts for 4-6 months.

As a Cohere Research Intern, You Will:

  • 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 your research results through the production of publications, datasets, and code.
  • Contribute to research initiatives that have practical applications in Cohere’s product development.

You May Be a Good Fit If You:

  • Are currently pursuing, or in the process of obtaining, a PhD in Machine Learning, NLP, Artificial Intelligence, or a related discipline. We will also consider exceptional non-PhD candidates.
  • Are eligible for work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout the internship period.
  • Have experience using large-scale distributed training strategies, data annotation and evaluation pipelines, or implementing state of the art ML models.
  • Are familiar with autoregressive sequence models, such as Transformers.
  • Have strong communication and problem-solving skills with the ability to convey complex research findings clearly and succinctly.
  • Have knowledge, or are knowledgeable, of programming languages such as Python, C, C++, Lua, or related languages.
  • Have knowledge of related ML frameworks such as JAX, Pytorch and Tensorflow.
  • Have previous experience in building systems based on machine learning and deep learning techniques.
  • Demonstrate passion for applied NLP models and products.

Preferred Qualifications:

  • Demonstrated expertise through publications in top tier venues in fields such as machine learning, NLP, artificial intelligence, computer vision, optimization, computer science, statistics, applied mathematics, or data science.
  • Proven ability to tackle analytical problems using quantitative methodologies.
  • Proficiency in handling and analysing complex, high-dimensional data from various sources.
  • Experience in applying theoretical and empirical research to real-world problem-solving.

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!

We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.

Full-Time Employees At Cohere Enjoy These Perks:

  • An open and inclusive culture and work environment.
  • Work closely with a team on the cutting edge of AI research.
  • Weekly lunch stipend, in-office lunches & snacks.
  • Full health and dental benefits, including a separate budget to take care of your mental health.
  • 100% Parental Leave top-up for up to 6 months.
  • Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement.
  • Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend.
  • 6 weeks of vacation (30 working days!).

Key skills/competency:

  • Machine Learning
  • Natural Language Processing (NLP)
  • Large Language Models (LLMs)
  • Deep Learning
  • Distributed Training
  • Research & Development
  • Python
  • PyTorch / JAX / TensorFlow
  • Data Evaluation
  • AI Product Development

Tags:

Research Intern
Machine Learning
NLP
Large Language Models
Deep Learning
AI
Data Science
Optimization
Python
JAX
PyTorch
TensorFlow
Transformers
Distributed Training
Evaluation
Finetuning
RAG
Multimodal Models
Applied Research
Publications

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How to Get Hired at Cohere

  • Research Cohere's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Highlight your PhD research, publications, and experience with ML frameworks and large language models for a Research Internship.
  • Showcase your projects: Detail relevant machine learning projects, code contributions, and any experience with distributed training or data pipelines.
  • Prepare for technical interviews: Be ready to discuss deep learning, NLP, Transformer architectures, and your research methodologies.
  • Demonstrate problem-solving: Practice articulating complex research findings and analytical approaches clearly and succinctly in interviews.

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