Time since we first saw it
Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
Employment type in the employer’s posting: InternFrom the employer’s posting
Design, train and improve cutting-edge models
Train extremely large-scale models on massive datasets
Help develop new techniques to train and serve models safer and faster
Explore continual and active learning strategies for streaming data
Work closely with product teams to develop solutions
Design, train and improve upon cutting-edge models.
Train extremely large-scale models on massive datasets.
Help us develop new techniques to train and serve models safer, better, and faster.
Explore continual and active learning strategies for streaming data.
Work closely with product teams to develop solutions.
you should be a student currently enrolled in a post-secondary program
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.
Open 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
9 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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.
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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).
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.
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.
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Canada
- 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.
No clear work-authorization passage found. Eligibility is unconfirmed.