Machine Learning Intern/Co-op (Winter 2027)

Cohere; Toronto; On-site; GBP 25,000 - 35,000; Full time

Benefits offered by this job

Weekly lunch stipend

Health and dental benefits

100% parental leave top-up

6 weeks of vacation

Remote-flexible work

Job summary

Cohere is looking for a Machine Learning Intern to join their team in the United Kingdom. This role involves designing and improving cutting-edge AI models, working with experienced staff, and contributing to innovative research. Applicants should be proficient in Python and familiar with various ML frameworks. The internship offers an open culture with benefits including health coverage, flexible work arrangements, and ample vacation time. This is an exciting opportunity for students passionate about AI and machine learning.

Qualifications

• Experience with large-scale distributed training strategies is a plus.
• Demonstrated communication and problem-solving skills are essential.
• Passion for applied NLP models and products preferred.

Responsibilities

• Design, train, and improve cutting-edge models.
• Develop techniques for safer and faster model training.
• Train large-scale models on massive datasets.
• Explore continual and active learning strategies.

Skills

Proficiency in Python

Experience with TensorFlow

Large-scale distributed training

Autoregressive sequence models knowledge

Strong communication skills

Passion for applied NLP

Education

Currently enrolled in a post-secondary program

Tools

CUDA

TPUs

Job description

Job Overview

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

Why this role?

Ship state‑of‑the‑art models to production. Design and implement novel research ideas. Build elegant training/deployment pipelines. Join us at a pivotal moment, shape what we build and wear multiple hats as an intern.

As a Machine Learning Intern, You Will

• Design, train and improve upon cutting‑edge models.
• Help us develop new techniques to train and serve models safer, better, and faster.
• Train extremely large‑scale models on massive datasets.
• Explore continual and active learning strategies for streaming data.
• Learn from experienced senior machine learning technical staff.
• Work closely with product teams to develop solutions.

You May Be a Good Fit If You Have

• Proficiency in Python and related ML frameworks such as TensorFlow, TF‑Serving, JAX, and XLA/MLIR.
• Experience using large‑scale distributed training strategies.
• Familiarity with autoregressive sequence models, such as Transformers.
• Strong communication and problem‑solving skills.
• A demonstrated passion for applied NLP models and products.
• Bonus: experience writing kernels for GPUs using CUDA.
• Bonus: experience training on TPUs.
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• Bonus: papers at top‑tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

Eligibility

To be eligible for this position you must be a student currently enrolled in a post‑secondary program, available for a full‑time 3‑6 month internship, co‑op, or research work term.

Benefits

• 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 and snacks.
• Full health and dental benefits, including a separate budget to take care of mental health.
• 100% parental leave top‑up for up to 6 months.
• Personal enrichment benefits towards arts, culture, fitness, 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).

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.