Machine Learning Intern/Co-op (Winter 2027)

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. 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. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! 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! Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage Please Note: To be eligible for this position you should 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. 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. Bonus: papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP). Full-Time Employees At Cohere Enjoy These Perks A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. Full health and dental benefits, including a separate budget for mental health. RRSP matching, 401K, Pension Scheme. 100% Parental Leave top-up for up to 6 months, for either parent. Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. 6 weeks of paid vacation (30 working days!) Budget for traveling to other offices if you are remote, plus an annual company offsite. How And Where We Work Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. For those not near an office: a co-working benefit so you can work alongside others in your city. Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We 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. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers page.

The intern will design, train, and improve cutting-edge large-scale models using massive datasets. They will also develop techniques for safer and faster model serving while collaborating with product teams to implement research ideas.

Candidates must be currently enrolled students proficient in Python and ML frameworks like JAX or TensorFlow with knowledge of Transformers. Experience in distributed training and a passion for applied NLP are highly valued.

• Weekly lunch stipend • Health benefits • Dental benefits • Mental health budget • RRSP matching • 401K • Pension Scheme • Parental Leave top-up • Arts & culture benefits • Fitness/wellness benefits • Quality time benefits • Workspace improvement credit • Education & learning stipend • 6 weeks paid vacation • Travel budget for remote employees • Annual company offsite • Home office stipend

• Résolution de problèmesSouhaitée
• CommunicationSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Python
• Tensorflow
• TF-Serving
• JAX
• XLA/MLIR
• Distributed Training
• Transformers
• NLP
• CUDA
• TPU Training
• Problem-solving
• Communication

• Technology
• Software
• Engineering
• Science & Research
• Data & Analytics

Formation minimale

Maîtrise

Expérience minimale

0+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Internship