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Internship Machine Learning Jobs in Montreal, QC

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

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 ...

D. degree in Artificial Intelligence, Machine Learning, Data Science, or a related field. * You ... or internship-are subject to a criminal background check. Positions that involve access to ...

Internship Machine Learning information

See Montreal, QC salary details

$19.9K

$108.3K

$211.9K

How much do internship machine learning jobs pay per year?

As of Sep 12, 2026, the average yearly pay for internship machine learning in Montreal, QC is $108,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,884.00 and $155,560.00 per year, depending on experience, location, and employer.

What is an internship machine learning?

Internship machine learning positions are temporary roles for students or recent graduates to gain hands-on experience in the field of machine learning. Interns typically work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced professionals. These internships provide valuable exposure to machine learning tools, programming languages such as Python, and industry best practices. They are an excellent way to build technical skills, enhance your resume, and explore career opportunities in artificial intelligence and data science.

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

As a Machine Learning intern, you may work on a variety of projects such as data preprocessing and cleaning, developing and testing machine learning models, or assisting with research experiments. These projects often involve collaborating closely with data scientists and engineers, learning to use popular frameworks like TensorFlow or PyTorch, and presenting your findings to the team. The scope and complexity of your assignments will typically grow as you demonstrate proficiency and initiative, providing valuable real-world experience and networking opportunities.

What are the key skills and qualifications needed to thrive as an internship machine learning?

To thrive as a Machine Learning Intern, you generally need a solid grounding in mathematics, programming (especially Python), and familiarity with machine learning concepts, often supported by coursework or relevant projects. Experience with tools and libraries like TensorFlow, scikit-learn, and Jupyter Notebooks, as well as knowledge of version control systems like Git, is typically expected. Strong problem-solving skills, willingness to learn, and effective communication set outstanding interns apart. These skills and qualities enable interns to contribute meaningfully to projects, adapt quickly, and collaborate well within technical teams.

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

AspectInternship Machine LearningData Science Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, programming, data analysis basics
Work EnvironmentHands-on ML model development, codingData analysis, visualization, reporting
Industry UsageTech, AI companies, research labsBusiness, finance, healthcare sectors

Internship Machine Learning focuses on developing and implementing machine learning models, requiring programming and ML fundamentals. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. Both roles are common in tech and research industries, but ML internships are more specialized in model building, while Data Science internships emphasize data analysis and visualization.

What are the most commonly searched types of Machine Learning jobs in Montreal, QC?

The most popular types of Machine Learning jobs in Montreal, QC are:

What are popular job titles related to Internship Machine Learning jobs in Montreal, QC?

For Internship Machine Learning jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Internship Machine Learning jobs in Montreal, QC look for?

The top searched job categories for Internship Machine Learning jobs in Montreal, QC are:

Infographic showing various Internship Machine Learning job openings in Montreal, QC as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 77% Full Time, 19% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $108,287 per year, or $52.1 per hour.

Machine Learning Scientist

Montreal, QC • On-site

Full-time

Medical, Dental, Vision

Re-posted 16 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!