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Machine Learning Intern Jobs in Ontario (NOW HIRING)

ShyftLabs

AI Engineer Intern

Toronto, ON · Hybrid

CA$20 - CA$30/hr

We are looking for an AI Engineer Intern interested in building production-ready AI agents and ... Good understanding of machine learning, natural language processing, and LLM fundamentals.

ARM

Intern Program - Engineering Pathways

Toronto, ON · Hybrid

Our intern program would suit candidates with interest across engineering -- from the hardware ... AI & Machine Learning -- Develop or optimize AI/ML solutions and apply technologies such as LLMs ...

Mackenzie Financial Corporation

CA$49K - CA$51K/yr

We are currently hiring an intern looking for a winter term position, January to April 2027, in our ... data for machine learning) * Analyze structured and unstructured data, organize findings and ...

Gerdau

INTERN

Whitby, ON · On-site

OCCUPATIONAL HEALTH AND SAFTEY INTERN Empowering people who build the future. POSITION ... This program is for individuals with high learning agility and willingness to adapt and develop ...

Merieux NutriSciences

Intern

Guelph, ON · On-site

Position Overview The intern performs technical procedures related to DNA analysis within ahigh-throughput laboratory environment. Primary responsibilities include samplepreparation, DNA extraction ...

Merieux NutriSciences

Intern

Guelph, ON · On-site

Position Overview The intern performs technical procedures related to DNA analysis within ahigh-throughput laboratory environment. Primary responsibilities include samplepreparation, DNA extraction ...

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All JobsMachine Learning Intern JobsMachine Learning Intern Jobs in Ontario

Machine Learning Intern information

See Ontario salary details

$9

$47

$88

How much do machine learning intern jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for machine learning intern in Ontario is $47.13, according to ZipRecruiter salary data. Most workers in this role earn between $38.46 and $52.64 per hour, depending on experience, location, and employer.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What does a machine learning intern do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

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

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What types of projects do machine learning interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

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

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

More about Machine Learning Intern jobs

What are the most commonly searched types of Machine Learning jobs in Ontario?

The most popular types of Machine Learning jobs in Ontario are:

What are popular job titles related to Machine Learning Intern jobs in Ontario?

For Machine Learning Intern jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Machine Learning Intern jobs in Ontario look for?

The top searched job categories for Machine Learning Intern jobs in Ontario are:

What cities in Ontario are hiring for Machine Learning Intern jobs?

Cities in Ontario with the most Machine Learning Intern job openings:

Machine Learning Intern jobs near you
Infographic showing various Machine Learning Intern job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $98,034 per year, or $47.1 per hour.

AI Engineer Intern

ShyftLabs

Toronto, ON • Hybrid

CA$20 - CA$30/hr

Internship

Re-posted 16 days ago

Key responsibilities

  • Build and improve agent orchestration and multi-agent workflows.

  • Develop agentic applications for enterprise use cases using Continuum.

  • Build APIs, backend services, and user-facing prototypes for agentic applications.

Job description

About ShyftLabs

At ShyftLabs, we live and breathe data. Since 2020, we've been helping Fortune 500 companies unlock growth through innovative digital solutions that drive real business impact. With teams across Canada, the U.S., and India, we're growing quickly and looking for curious, motivated individuals who are excited to learn, build, and solve meaningful problems with technology.

About Continuum

Continuum is an enterprise AI agent execution and control platform designed to help teams build, run, and deploy reliable agentic applications. It provides agent orchestration, multi-model routing, persistent memory, tool integration, durable workflows, governance, guardrails, evaluation, and observability.

We are looking for an AI Engineer Intern interested in building production-ready AI agents and applications. You will contribute to the Continuum platform while also using it to build agentic applications for real enterprise use cases.

This is a hands-on engineering role. You will work across agent orchestration, memory systems, model optimization, retrieval, tools, guardrails, evaluation, and application development.

What You'll Be Doing

  • Build and improve agent orchestration and multi-agent workflows.

  • Develop agentic applications for enterprise use cases using Continuum.

  • Work with different commercial and open-source models, including OpenAI, Anthropic, Gemini, Llama, Qwen, Mistral, and others.

  • Improve intelligent model routing based on task complexity, quality, latency, and cost.

  • Build persistent memory and state-management capabilities for long-running agent workflows.

  • Develop tool-calling functionality and integrations with APIs, databases, and enterprise systems.

  • Work with MCP servers and function tools to connect agents with external services.

  • Design context-engineering and retrieval pipelines using vector and graph databases.

  • Implement AI guardrails for safety, security, access control, data privacy, and policy enforcement.

  • Create evaluation pipelines to measure accuracy, groundedness, hallucination, tool usage, workflow completion, latency, and cost.

  • Improve the observability and traceability of agent decisions, tool calls, and workflow execution.

  • Optimize prompts, model usage, token consumption, response time, and infrastructure costs.

  • Build APIs, backend services, and user-facing prototypes for agentic applications.

  • Write clean, reusable, well-tested, and documented Python code.

  • Contribute to Continuum's open-source codebase, examples, documentation, and developer experience.

What We Are Looking For

  • Currently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.

  • Strong programming skills in Python.

  • Good understanding of machine learning, natural language processing, and LLM fundamentals.

  • Experience building at least one LLM-powered or agentic application.

  • Familiarity with prompt engineering, embeddings, RAG, tool calling, and structured outputs.

  • Experience working with APIs, Git, databases, and standard software engineering practices.

  • Ability to research complex technical problems, experiment with different approaches, and clearly communicate results.

  • Strong interest in building reliable AI systems, not just basic LLM demos

Nice to Have

  • Experience with agent frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI, or similar technologies.

  • Familiarity with OpenAI, Anthropic, Gemini, AWS Bedrock, or open-source models.

  • Experience with vector databases such as Milvus, Pinecone, Weaviate, or Chroma.

  • Experience with graph databases such as Neo4j.

  • Knowledge of PostgreSQL, Redis, Docker, Kubernetes, or cloud infrastructure.

  • Familiarity with AI observability and evaluation tools such as Langfuse.

  • Understanding of multi-tenancy, identity management, authorization, or enterprise security.

  • Experience with model routing, inference optimization, prompt compression, or cost optimization.

  • Contributions to open-source AI projects, research, hackathons, or technically strong personal projects.

Hourly Pay
  • $20 - $30/Hr (CAD)
Why You'll Love Working at ShyftLabs
 
At ShyftLabs, your work matters. We're a growing data product company making a big impact with Fortune 500 clients and as we scale, you'll have the chance to shape solutions, influence strategy, and grow your career alongside us.
 
Here's what you can expect when you join our team:
-Hybrid Flexibility: Enjoy a hybrid model with three days per week in our Toronto office.
-Downtown Toronto Office: Work in the heart of the city.
-Growth & Learning: Access extensive learning and development resources to keep leveling up your skills.
 
Inclusion at ShyftLabs
 
We're building something big, and we want you on the journey with us. If you're ready to use data and innovation to make an impact, apply today and let's grow together.
 
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse, and inclusive environment. We encourage applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, and nationality to apply. If you require accommodation during the interview process, let us know and we'll be happy to support you.
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