Machine Learning Intern/Co-op - Winter 2027

SpeedyApply LLC; San Francisco (CA); On-site; USD 40,000 - 60,000; Full time

Benefits offered by this job

Weekly lunch stipend

Full health benefits

Family/Parental leave

Conference & learning stipend

Home office stipend

Job summary

Cohere is a leading security-first enterprise AI company building foundation models and end-to-end products to solve real-world business problems. We’re hiring a Machine Learning Intern to ship state-of-the-art models to production and design novel training/deployment pipelines.

As an intern, you will design and train models, explore new learning strategies for streaming data, and collaborate with product teams to deliver practical NLP solutions.

Qualifications

• 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 (NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

Responsibilities

• 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.

Skills

Python

TensorFlow

JAX

XLA/MLIR

Distributed training

Transformers

Communication

NLP interest

CUDA

TPU

Tools

TF-Serving

Job description

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.

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.