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Machine Learning Summer Internship Jobs in Quebec

... internships. Additional capabilities include: * Strong foundation in machine learning fundamentals, statistics, and experimental reasoning. * Strong Python skills and experience with common ML/data ...

CA$96K - CA$128K/yr

AI Machine Learning Engineer, Level 17 or 18 Employment Type:Permanent Compensation Details ... We have hybrid work options, 3 to 4 weeks paid vacation, a corporate closure period, summer early ...

New

CA$96K - CA$128K/yr

AI Machine Learning Engineer, Level 17 or 18 Employment Type: Permanent Compensation Details ... We have hybrid work options, 3 to 4 weeks paid vacation, a corporate closure period, summer early ...

CA$96K - CA$128K/yr

AI Machine Learning Engineer, Level 17 or 18 Employment Type:Permanent Compensation Details ... We have hybrid work options, 3 to 4 weeks paid vacation, a corporate closure period, summer early ...

New

CA$96K - CA$128K/yr

AI Machine Learning Engineer, Level 17 or 18 Employment Type: Permanent Compensation Details ... We have hybrid work options, 3 to 4 weeks paid vacation, a corporate closure period, summer early ...

Must be an active student during your internship and/or returning to school in next Summer or Fall ... At least one previous internship in data science, artificial intelligence, machine learning, or ...

New

Make your internship count At Intelcom, interns don't just observe, they contribute meaningfully to ... Apply AI and machine learning techniques to develop and evaluate predictive models * Communicate ...

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Machine Learning Summer Internship information

What is a machine learning summer internship?

A Machine Learning Summer Internship is a temporary, typically 8-12 week program for students or recent graduates to gain practical experience in machine learning. Interns work under the supervision of experienced professionals, contributing to real-world projects involving data analysis, model development, and algorithm implementation. These internships often provide mentorship, networking opportunities, and exposure to the latest tools and technologies in the field. They are valuable for building technical skills and improving career prospects in artificial intelligence and data science.

What types of projects can I expect to work on during a machine learning summer internship?

As a Machine Learning Summer Intern, you can expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of algorithms into production environments. Interns often work alongside data scientists and engineers on real-world datasets to solve business problems, develop prototypes, or improve existing models. This hands-on experience will help you gain practical skills in using popular ML frameworks and understanding the end-to-end machine learning workflow.

What are the key skills and qualifications needed to thrive as a machine learning summer intern, and why are they important?

To thrive as a Machine Learning Summer Intern, you need a solid background in mathematics, statistics, and programming (especially Python), often supported by ongoing coursework in computer science or related fields. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems such as Git, and data analysis tools is typically required. Strong problem-solving skills, curiosity, and teamwork are important soft skills that help interns contribute effectively and learn quickly. These skills and qualities are crucial for applying theoretical knowledge, collaborating on real projects, and adapting to the fast-evolving field of machine learning.

What is the difference between Machine Learning Summer Internship vs Data Science Summer Internship?

AspectMachine Learning Summer InternshipData Science Summer Internship
Required CredentialsBasic programming, math, and machine learning knowledgeProgramming, statistics, and data analysis skills
Work EnvironmentDeveloping ML models, algorithms, and prototypesData analysis, visualization, and reporting
Industry UsageTech companies, AI startups, research labsBusiness, finance, healthcare, tech firms

Both internships involve working with data and require programming skills, but Machine Learning Summer Internships focus on developing algorithms and models, while Data Science Summer Internships emphasize data analysis and insights. The choice depends on your interest in building models versus analyzing data.

What are popular job titles related to Machine Learning Summer Internship jobs in Quebec?

For Machine Learning Summer Internship jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Machine Learning Summer Internship jobs in Quebec look for?

The top searched job categories for Machine Learning Summer Internship jobs in Quebec are:

What cities in Quebec are hiring for Machine Learning Summer Internship jobs?

Cities in Quebec with the most Machine Learning Summer Internship job openings:

Infographic showing various Machine Learning Summer Internship job openings in Quebec as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 21% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Machine Learning Scientist

Montreal, QC • On-site

Full-time

Medical, Dental, Vision

Re-posted 17 days ago


Job description

About us

Eli Health is making continuous hormone monitoring possible so users can support their daily and long-term health. No more waiting days to track key biomarkers—get results you can use within minutes. Eli’s flagship product, Hormometer®, is the first instant hormone monitoring platform to deliver results from saliva to mobile app—anytime, anywhere.

Developed over six years of R&D, over 2,000 product iterations, and backed by a dozen patent-pending innovations, Eli’s award-winning platform turns hormones into measurable signals you can track and improve. Just as the thermometer and glucometer have transformed health for millions, Eli’s platform is poised to be the next major evolution in tracking changes in stress, endurance, sleep, and more.

About the role

Eli is looking for an on-site Applied Machine Learning Scientist to join our ML team and help solve challenging real-world problems involving imperfect, noisy, and complex datasets.

This role is primarily about scientific problem solving and applied machine learning, not ML infrastructure. You will work closely with the ML lead, who will support integration and productionization of your work

Where you'll spend the first half of your time

You’ll work on open-ended scientific and machine-learning problems, turning imperfect real-world data into robust, reproducible analyses and models. The results of these analyses will have to be communicated effectively to the broader team. The focus is on understanding the problem deeply, choosing the right methods, and validating that improvements are real and generalizable.

  • Explore datasets and understand the underlying data-generating processes.

  • Develop, evaluate, and improve machine learning, signal processing, and statistical models.

  • Perform feature engineering, model selection, validation, and error analysis.

  • Identify issues such as confounding, data leakage, measurement variability, and distribution shift.

  • Design experiments and analyses to resolve uncertainty and guide modelling decisions.

  • Investigate new modelling approaches, including classical ML and deep learning (when appropriate).

  • Produce clear, reproducible Python code that isn’t limited to notebooks, and communicate findings to technical and non-technical stakeholders.


Where you'll spend the other half

You’ll stay closely connected to how models behave in the real world. You’ll investigate production performance, diagnose failures and unexpected behavior, and use those observations to drive new analyses, experiments, and model improvements.

  • Develop analyses and models with the expectation that it will be deployed into production.

  • Investigate model performance and failures using real-world production data.

  • Perform ongoing error analysis, diagnostics, and root-cause investigations.

  • Identify distribution shifts, edge cases, systematic biases, and degradation in model performance.

  • Translate production observations into experiments, improvements, or data-collection strategies.

What we are looking for

Someone with a bachelor's degree (Master’s or PhD preferred) in Engineering, Computer Science, Data Science, Mathematics, or a related field who possesses a minimum of 5 years of professional experience excluding internships. Additional capabilities include:

  • Strong foundation in machine learning fundamentals, statistics, and experimental reasoning.

  • Strong Python skills and experience with common ML/data science libraries.

  • Ability to work independently on ambiguous problems and determine what questions need to be answered.

  • Good understanding of model validation, uncertainty, bias/variance, and generalization.

  • Ability to distinguish between improvements that are statistically or scientifically meaningful and those that simply improve a metric.

Above all, we are looking for someone who is particularly good at answering the following question:

Given the data we have and the problem we are trying to solve, what can we conclude with confidence, what remains uncertain, and what should we do next?

Why you’ll love working at Eli

  • You’ll work with a group of talented and mission-driven people eager to improve lifelong health at scale.

  • You’ll be part of the core team developing and commercializing the first product that monitors hormonal data daily and over a lifetime.

  • You’ll join the early-stage startup phase and have a wide-reaching impact in a constantly evolving, fast-paced environment.

  • You’ll be part of a small (<25 people), high-performing, and diverse team where everything you do results in tangible impact and shapes the company’s trajectory.

  • You’ll be in an environment where people drive their own work, think creatively about open-ended problems, and solve them proactively.

  • You’ll get health insurance (medical, dental, vision, and more) to ensure you and your family stay physically and mentally at your best.

  • You’ll have flexibility over your schedule and vacations. We seek to hire great people, then give them the autonomy and space they need to achieve their goals.

  • Although our office and R&D facilities are in Montreal, we have a distributed team. We prioritize asynchronous workflows and minimize meetings to focus on the work itself.

  • You and your +1 will have unlimited free access to the Bota Bota spa in Montreal to recharge.

How to apply

Sounds like you? Please apply using this link:https://jobs.ashbyhq.com/eli. Please note that we will not review applications made through other platforms. We look forward to learning about you!