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Internship For Machine Learning Jobs in Toronto, ON

Red Hat AI Inference team accelerates AI for the enterprise and brings operational simplicity to ... As a Machine Learning Engineer focused on model optimization algorithms, you will work closely with ...

Lead Machine Learning Engineer

Toronto, ON ยท Remote

$225K - $260K/yr

We're looking for talented individuals who will grow robotic deliveries from surprising novelty to ... We are solving real-world problems leveraging robotics, machine learning and computer vision, among ...

Senior Machine Learning Engineer

Toronto, ON ยท On-site

CA$84K - CA$128K/yr

Serve as a primary technical lead for client engagements focused on ML solution delivery. * Translate business goals into machine learning strategies and operational plans. * Collaborate with cross ...

Serve as a primary technical lead for client engagements focused on ML solution delivery. * Translate business goals into machine learning strategies and operational plans. * Collaborate with cross ...

Senior Machine Learning Engineer

Toronto, ON ยท On-site

CA$170K - CA$250K/yr

Layer 6 is the AI center of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people ...

Layer 6 is the AI research centre of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more ...

Layer 6 is the AI research centre of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more ...

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Internship For Machine Learning information

What types of projects and responsibilities can I expect during a Machine Learning internship?

As a Machine Learning intern, you'll typically work on data preprocessing, exploratory data analysis, model development, and performance evaluation under the guidance of experienced engineers or data scientists. Your daily tasks might include cleaning datasets, experimenting with different algorithms, and collaborating with team members to refine models for real-world applications. Interns often participate in regular team meetings, code reviews, and may present findings to stakeholders. This hands-on experience not only builds your technical skills but also helps you understand how machine learning solutions are integrated into business processes.

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

To thrive as a Machine Learning Intern, you need a solid understanding of mathematics, statistics, and programming languages such as Python, supported by coursework or a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, and experience with data analysis tools are typically expected. Analytical thinking, curiosity, and effective communication help interns excel in collaborative, fast-paced environments. These skills enable interns to contribute meaningfully to projects, learn quickly, and adapt to evolving challenges in machine learning.

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

AspectInternship For Machine LearningData Science Intern
Required SkillsProgramming (Python, R), ML algorithms, data preprocessingStatistics, data analysis, programming, visualization
Work EnvironmentDeveloping ML models, algorithm tuning, model deploymentData analysis, reporting, insights generation
Industry UsageTech, AI startups, research labsBusiness, finance, healthcare, tech

Internship For Machine Learning focuses on developing and deploying machine learning models, requiring skills in algorithms and programming. Data Science Internships emphasize analyzing data, generating insights, and reporting. Both roles often overlap but serve different core functions within data-driven projects.

What is an internship for machine learning?

An internship for machine learning is a temporary position offered to students or recent graduates who want to gain practical experience working with machine learning algorithms, models, and data. Interns typically work under the supervision of experienced engineers or data scientists and are involved in tasks such as data preprocessing, building and training models, and evaluating their performance. These internships provide hands-on exposure to tools, libraries, and real-world projects, helping interns develop valuable technical and problem-solving skills. Machine learning internships are commonly found in tech companies, research labs, and startups.
Infographic showing various Internship For Machine Learning job openings in Toronto, ON as of June 2026, with employment types broken down into 1% Internship, 1% As Needed, 76% Full Time, 20% Part Time, 1% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.
Machine Learning Platform Engineer

Machine Learning Platform Engineer

Royal Bank of Canada

Toronto, ON โ€ข On-site

Full-time

Posted 13 days ago


Job description

Job Description

What's the opportunity?

We're looking for an experienced Machine Learning Platform Engineer who will bring focus and subject-matter expertise around designing and implementing machine learning infrastructure and automation tools (MLOps and DevOps). This is a unique opportunity to grow in the world of machine learning infrastructure and work with a team of passionate individuals committed to the mission of bringing ML to enterprise.

At RBC Borealis, you'll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at rbcborealis.com.

Your responsibilities include:

  • Deploying and operating the GenAI platform across OpenShift/Kubernetes;

  • Managing large language model deployments (Cohere Command, Llama, Mistral) on GPU infrastructure (NVIDIA A100/H100), and configuring RAG pipelines with serving frameworks like vLLM, NVIDIA NIM, and TensorRT-LLM;

  • Monitoring GPU utilization, model performance metrics, and resource allocation across the platform;

  • Implementing observability stacks-Prometheus, Grafana, Pushgateway, and structured logging pipelines-to surface platform health, performance, and security signals;

  • Designing and implementing best practices and standards for data and machine learning pipelines across the organization;

  • Supporting platform users and cross-functional teams through infrastructure design guidance, thorough documentation, and collaboration across multiple RBC locations;

  • Building highly scalable, resilient on-premise systems for hosting machine learning systems using state-of-the-art technologies;

You're our ideal candidate if you have:

  • Strong experience designing and operating distributed/ML systems plus deep Kubernetes/OpenShift knowledge (Helm, operators, custom resources, RBAC, troubleshooting);

  • Proven history building DevOps/CI/CD pipelines (GitHub Actions), multi-stage Docker images, registry mirroring, and infrastructure automation in restricted enterprise environments;

  • In-depth knowledge of various stages of the machine learning application deployment process;

  • Proficiency with programming languages such as Python, Bash, or Rust;

  • Solid grasp of software engineering best practices-testing (unit/integration), coding standards, code reviews, source control-and implementing production monitoring, alerting;

  • Hands-on experience building and deploying hybrid environments on-premises enterprise environments;

  • Familiarity with the Large Language Model (LLM) inference and serving such as VLLM or similar;

What's in it for you?

  • Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;

  • Leaders who support your development through coaching and managing opportunities;

  • Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis is the driving force behind Royal Bank of Canada's AI and data innovation. As part of Canada's largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we're at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

#TechPJ
#LI-Post

Job Skills

Big Data Management, Data Mining, Data Science, Deep Learning, DevOps, Machine Learning (ML), Machine Learning Operations, Programming Languages

Additional Job Details

Address:

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-02-18

Application Deadline:

2026-06-30

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Employment Type: FULL_TIME