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Machine Learning Engineer Intern Jobs in Markham, ON

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful insights that drive strategic decision-making. The Opportunity Summary We are seeking an experienced ...

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and ...

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful insights that drive strategic decision-making. The Opportunity Summary We are seeking an experienced ...

Day-to-day as a Machine Learning Engineer: * Join a world-class team of AI developers with an extensive track record. * Architect scalable machine learning and Gen AI systems that integrate with ...

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

The Opportunity We're hiring a Staff Machine Learning Engineer to join our AI team and help shape the next generation of Fullscript's AI-powered experiences. You'll work on building innovative AI ...

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Showing results 1-20

Machine Learning Engineer Intern information

See Markham, ON salary details

$21.8K

$114.4K

$204.2K

How much do machine learning engineer intern jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning engineer intern in Markham, ON is $114,388.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,001.00 and $155,372.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What job categories do people searching Machine Learning Engineer Intern jobs in Markham, ON look for? The top searched job categories for Machine Learning Engineer Intern jobs in Markham, ON are:
What cities near Markham, ON are hiring for Machine Learning Engineer Intern jobs? Cities near Markham, ON with the most Machine Learning Engineer Intern job openings:
Infographic showing various Machine Learning Engineer Intern job openings in Markham, ON as of May 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Hybrid job distribution, with an average salary of $114,388 per year, or $55 per hour.
Machine Learning Engineer

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


United Airlines rating

7.8

Company rating: 7.8 out of 10

Based on 331 frontline employees who took The Breakroom Quiz

9th of 26 rated airlines


Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Job Description
What's in it for you
  • We thrive on the challenge to be our best progressive thinking to keep growing and working together to deliver trusted advice to help our clients thrive and communities prosper.
  • We care about each other reaching our potential making a difference to our communities and achieving success that is mutual
  • A comprehensive Total Rewards Program including bonuses and flexible benefits competitive compensation and stock where applicable
  • Leaders who support your development through coaching and meaningful opportunities for growth
  • The ability to make a lasting impact on how our Sales teams compete and win business at scale
  • Work in a dynamic collaborative and high performing team tackling some of the most challenging AI problems in financial services sales
  • A worldclass training program in financial services and AI best practices. 
  • Access to challenging work and the chance to build close relationships with Sales leadership and clients
What do you need to succeed
  • A PhD or Master's degree in Computer Science Machine Learning Deep Learning or equivalent hands on experience
  • Five or more years building Deep Learning or Machine Learning models in production environments
  • Advanced proficiency in Python and hands on experience with Generative AI frameworks and architectures
  • Deep knowledge of retrieval augmented generation RAG agentic frameworks context and memory management and tool skills integration patterns
  • Strong understanding of large language model architectures inference finetuning and model deployment
  • Experience with Anthropic models and Claude including code generation capabilities
  • In-depth knowledge of embeddings re-rankers and vector databases
  • Expertise in ML experimentation model evaluation and monitoring in production
  • Strong foundation in algorithms data structures and distributed computing
  • Understanding of sales workflows client intelligence use cases or familiarity with how sales teams operate
  • Embrace of AIfirst approach Actively incorporates AI tools and technologies into daily workflows to enhance productivity streamline routine tasks and drive efficiency Demonstrates curiosity about emerging AI capabilities and applies them thoughtfully to deliver better outcomes for clients and internal stakeholders.
What will you do
  • Design and build agentic frameworks that solve critical sales use cases including client intelligence gathering pitch content generation deal summarization and Realtime conversation analysis.
  • Develop conversational AI systems that assist sales professionals in client interactions and help synthesize client intelligence across multiple data sources.
  • Embed Generative AI tools into Sales platforms enabling seamless workflows for prospect research proposal generation and deal tracking Architect end to end AI solutions covering experimentation model evaluation and production monitoring to ensure sales tools perform reliably at scale.
  • Guide the team on best practices conduct code reviews and mentor team members on Generative AI implementation.

The base compensation range for this role in the posted location is: 67,000 to 83,000.

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: 

  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect.  We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States.  http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.


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About United Airlines

Sourced by ZipRecruiter

United Airlines is embarking on an exciting journey to become the best airline in aviation history. Our purpose, "Connecting People, Uniting the World," extends beyond transportation, emphasizing our commitment to uplift and create opportunities in the places we serve. With a global presence and diverse workforce, we value inclusivity and are dedicated to hiring tens of thousands of individuals across various roles. Our comprehensive benefits package, including perks like space available travel, parental leave, and 401k, aims to support your well-being and growth.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1926

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