Research Internship (Winter 2027)
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- Stated location
- Canada
- Listing updated on our site
- 14 Nov 2026, 00:01 EAT
Last seen in the live employer feed: 14 Nov 2026, 00:00 EAT. This confirms a feed listing, not employer endorsement of an application.
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| Employer | Verified Direct Employer (Protected) |
|---|---|
| Location | Canada |
| Remote type | Remote |
| Posted | 6mo ago |
| Application Status | Pro Membership & Free Pass Access |
About this role (Direct Employer Details Protected)
Who are we?
[Employer] 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. [Employer] 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?
To have the opportunity to collaborate with [Employer] 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 [Employer] 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 [Employer]’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.
Full-Time Employees at [Employer] 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:
- [Employer] 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: [Employer] 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 [Employer] careers page and LinkedIn only, with all communications from [Employer] employees coming from an @[Employer].com or @cw.[Employer] email alias. If jobs are viewed on other sites then please verify these through our official careers page.
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