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Machine Learning Remote Internship Jobs in Toronto, ON

Xiopt

Marketing Intern

Toronto, ON · Remote

Role Description This is a full-time, remote Internship role in Marketing. Interns will engage in ... Passion for continuous learning and a proactive approach to professional growth.

Waabi

Research Scientist, Learnable Planner

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

Qualifications: - MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ... internships, work experience, research projects, and papers at top conferences. - Strong ...

Mercor

Network Specialist - Fully Remote

Toronto, ON · Remote

CA$50 - CA$70/hr

Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from deployed ... Curiosity about how raw infrastructure data becomes machine learning input. Application Process ...

THOMSON REUTERS

Lead Research Engineer

Toronto, ON · On-site +1

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

Waabi

Research Scientist, Simulation Agents

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

... interns; foster a culture of scientific rigor and rapid experimentation. - Publish high-impact research at top-tier conferences in machine learning or robotics. Qualifications: - Masters/PhD in ...

DataVisor

Delivery Engineer - Canada

Toronto, ON · Remote

CA$80K - CA$120K/yr

Exposure to real-time computing, big data technologies, or machine learning through coursework, internships, or project experience is a plus. Benefits 1. Health Insurance, PTO, stock option 2. The ...

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All JobsMachine Learning JobsMachine Learning Remote Internship JobsMachine Learning Remote Internship Jobs in Toronto, ON

Machine Learning Remote Internship information

What types of projects can I expect to work on during a Machine Learning Remote Internship?

During a remote machine learning internship, you can expect to contribute to projects such as data preprocessing, model development, and performance evaluation. Interns often work on real-world datasets, applying techniques like regression, classification, clustering, or deep learning, depending on the organization's focus. Collaboration with data scientists, engineers, and other interns is common, typically via virtual meetings and shared code repositories. These projects provide hands-on experience and often culminate in presenting your findings to the team, offering valuable exposure to industry-standard workflows and tools.

What is a Machine Learning Remote Internship?

A Machine Learning Remote Internship is a temporary, structured work experience where interns contribute to machine learning projects from a remote location, such as their home. Interns typically work with teams on tasks like data preprocessing, building models, and evaluating results, while gaining practical knowledge and mentoring. These internships are ideal for students or recent graduates looking to develop their skills in machine learning, programming, and data science without the need to relocate. They often involve working with Python, popular ML libraries, and real-world datasets. Communication and collaboration are maintained through online tools and regular meetings.

What are the key skills and qualifications needed to thrive as a Machine Learning Remote Intern, and why are they important?

To thrive as a Machine Learning Remote Intern, you need a solid background in programming (especially Python), mathematics/statistics, and a foundational understanding of machine learning concepts, often gained through coursework or relevant projects. Familiarity with machine learning libraries (like TensorFlow, PyTorch, and scikit-learn), version control systems (such as Git), and cloud platforms is typically expected. Strong problem-solving abilities, self-motivation, and effective remote communication set top interns apart. These skills and qualities enable efficient collaboration, successful project delivery, and continuous learning in a dynamic, distributed work environment.

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

AspectMachine Learning Remote InternshipData Science Intern
Required CredentialsBasic programming, math, and machine learning knowledgeStatistics, programming, and data analysis skills
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis and modeling tasks
Industry UsageTech, AI, startups, research labsTech, finance, healthcare, consulting
Search & Comparison IntentUnderstanding internship roles in MLExploring data science internship opportunities

Machine Learning Remote Internships focus on developing models and algorithms, often requiring knowledge of programming and math. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. While both roles are remote and industry-relevant, ML internships emphasize algorithm development, whereas data science roles focus on data analysis and visualization.

What are popular job titles related to Machine Learning Remote Internship jobs in Toronto, ON? For Machine Learning Remote Internship jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Machine Learning Remote Internship jobs in Toronto, ON look for? The top searched job categories for Machine Learning Remote Internship jobs in Toronto, ON are:
Machine Learning Remote Internship jobs near you
Infographic showing various Machine Learning Remote Internship job openings in Toronto, ON as of June 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 100% Remote job distribution.

Applied ML Researcher - Fully Remote | Upto $90/hr

Mercor

Toronto, ON • Remote

CA$90/hr

Full-time

Posted 4 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Machine Learning Engineer Expert
Type: Contract
Compensation: $90/hour
Location: Remote

Role Responsibilities

  • Develop end-to-end machine learning solutions for challenging prediction and modeling problems.
  • Analyze datasets and define appropriate modeling approaches, validation strategies, and evaluation metrics.
  • Perform exploratory data analysis, feature engineering, and data preprocessing.
  • Train, tune, and evaluate machine learning models across tabular, text, image, and time-series datasets.
  • Review and validate the technical quality of machine learning projects and deliverables.
  • Identify opportunities to improve model performance through systematic experimentation and iteration.

Qualifications

Must-Have

  • Master's degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field from a top-tier university.
  • 2+ years of professional experience in machine learning, applied AI, data science, or a closely related field.
  • Strong proficiency in Python and modern machine learning frameworks (e.g., scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow).
  • Demonstrated experience building end-to-end machine learning solutions, including data preparation, model development, validation, and evaluation.
  • Strong understanding of model evaluation metrics, validation methodologies, and experimental design.
  • Experience with one or more of the following areas: tabular machine learning, natural language processing, computer vision, recommendation systems, ranking systems, time-series forecasting.
  • Ability to work independently on open-ended machine learning problems and deliver high-quality technical outputs.

Preferred

  • PhD from a leading research university.
  • Experience at leading technology companies, AI labs, research institutions, or high-growth startups.
  • Participation in competitive machine learning or data science competitions.
  • Experience optimizing models against performance-based evaluation metrics.
  • Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning.
  • Publications, patents, or significant open-source contributions in machine learning or AI.
  • Experience reviewing, mentoring, or evaluating the work of other machine learning practitioners.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.