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Internship Deep Learning Jobs in Toronto, ON (NOW HIRING)

Scotiabank

Senior Scrum Master

Scarborough, ON · On-site

Would you like to complete your internship with an organization that has been in the market for ... Deep knowledge of Agile frameworks (Scrum, Kanban, XP, Lean) and scaling approaches (SAFe, LeSS, or ...

Mars

Food Safety Specialist - Pet Nutrition

Bolton, ON · On-site

The Food Safety Specialist provides deep technical leadership to develop, maintain and proactively ... field and internship in quality and food safety in a manufacturing environment. * 2-3 years of ...

New

Waabi

Research Scientist, World Models

Toronto, ON · On-site +1

CA$155K - CA$269K/yr

Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. ... D. in Computer Vision, Machine Learning, Robotics, or a related field or equivalent research ...

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All JobsDeep Learning JobsInternship Deep Learning JobsInternship Deep Learning Jobs in Toronto, ON

Internship Deep Learning information

What is an internship in deep learning?

An internship in deep learning is a temporary position, typically offered to students or recent graduates, where individuals gain practical experience working on projects involving neural networks, machine learning algorithms, and AI applications. Interns often assist with data preparation, model training, evaluation, and sometimes contribute to research or development of deep learning solutions. This role helps interns develop technical skills, gain exposure to real-world problems, and build a foundation for a career in artificial intelligence or related fields.

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

AspectInternship Deep LearningData Science Intern
Required SkillsMachine learning, neural networks, programming (Python, TensorFlow)Statistics, data analysis, programming (Python, R)
Work EnvironmentResearch-focused, AI/ML teams, tech companiesBusiness analytics, data analysis teams, various industries
Common Employer UsageTech firms, AI startups, research labsConsulting firms, tech companies, finance, healthcare

Internship Deep Learning roles focus on developing neural networks and AI models, often in research or tech environments. Data Science Internships involve analyzing data, creating insights, and supporting decision-making across diverse industries. Both internships require programming skills, but Deep Learning emphasizes AI-specific knowledge, while Data Science covers broader data analysis skills.

What types of projects or tasks can I expect to work on during a deep learning internship?

As a Deep Learning intern, you can typically expect to work on a variety of hands-on projects such as data preprocessing, model development, and performance evaluation. You may contribute to building and testing neural networks, experimenting with architectures like CNNs or RNNs, and assisting in preparing datasets for training. Collaboration with data scientists, engineers, and other interns is common, providing opportunities to learn best practices in model deployment and documentation. This role offers a valuable chance to gain practical experience in applying theoretical knowledge to real-world problems.

What are the key skills and qualifications needed to thrive in a deep learning internship, and why are they important?

To thrive in a Deep Learning Internship, you need a strong foundation in mathematics, programming (especially Python), and machine learning concepts, typically supported by ongoing or completed studies in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience using tools like Jupyter Notebook are highly valued. Strong problem-solving skills, curiosity, and effective communication help interns stand out when working on complex projects and collaborating with teams. These skills and qualities are crucial for efficiently developing, testing, and explaining deep learning models in a fast-evolving field.
What are popular job titles related to Internship Deep Learning jobs in Toronto, ON? For Internship Deep Learning jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Internship Deep Learning jobs in Toronto, ON look for? The top searched job categories for Internship Deep Learning jobs in Toronto, ON are:
Internship Deep Learning jobs near you
Infographic showing various Internship Deep Learning job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 28% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Software Developer - Cloud Solutions

PulseLearning

Toronto, ON • On-site, Remote

$40 - $85/hr

Contractor

Posted 13 days ago

Job description

About PulseLearning

Established in 1999, PulseLearning is a world-class, award-winning provider of learning solutions supporting clients globally across all sectors.

We operate across the United States, United Kingdom, EMEA, Ireland, Canada, and Australia, delivering innovative, people-focused learning solutions that drive real impact.

Our team works collaboratively to design and develop learning experiences that inspire behavioral change and measurable results. At PulseLearning, we value creativity, collaboration, and continuous improvement.


Role Overview

The Software Developer will be part of a team designing, building, and maintaining modern, cloud-based software solutions in collaboration with cross-functional teams and subject matter experts. The successful candidate will bring strong software engineering fundamentals, hands-on cloud experience, and a builder's mindset to deliver scalable, secure, and reliable systems.


Remote Work Term position, 3-9 months (duration set by client requirements)

Full-time (40 hrs/week) and part-time (20 hrs/week) positions available


Key Responsibilities

  • Contribute to a team that develops or enhances, tests, and deploys scalable, secure, and cost-effective software solutions using cloud-native architectures and microservices
  • Contribute to a team that develops software using one or more modern programming languages such as Java, Python, TypeScript, Go, C#, C++, or Rust
  • Contribute to a team that designs and consume RESTful APIs and integration frameworks to enhance system interoperability
  • Contribute to a team that deploys and operate workloads on major cloud platforms, applying cloud services for compute, storage, databases, networking, serverless, and containers
  • Contribute to a team that defines and manages infrastructure as code and automated deployment pipelines (CI/CD)
  • Apply engineering best practices, including automation, unit and integration testing, code reviews, secure coding, and technical documentation
  • Work with both relational (SQL) and NoSQL database technologies, selecting the right data store for each workload
  • Leverage AI agents, generative AI, and AI-enabled developer tools to improve development productivity and code quality
  • Monitor, troubleshoot, and resolve production issues, contributing to operational excellence and continuous improvement
  • Collaborate with cross-functional stakeholders and subject matter experts to translate business requirements into technical solutions
  • Contribute to a team that manages multiple development activities concurrently while meeting project timelines and quality standards
  • Work effectively with remote and globally distributed teams across multiple time zones
  • Be current with cloud technologies, architectural patterns, AI-assisted development practices, and emerging industry trends


Qualifications

  • 3+ years of professional (non-internship) software development experience
  • 2+ years of experience with design or architecture of new and existing systems, including design patterns, reliability, and scaling
  • Strong proficiency in at least one modern programming language (e.g., Java, Python, TypeScript, Go, C#, C++, or Rust)
  • Solid computer science fundamentals, including data structures, algorithms, and object-oriented design principles
  • Hands-on experience building and operating solutions on a major public cloud platform; deep familiarity with AWS services and architecture best practices is strongly preferred
  • Experience with distributed systems, microservices, serverless architectures, and containerization (e.g., Docker, Kubernetes)
  • Experience with infrastructure as code (e.g., CloudFormation, CDK, or Terraform) and CI/CD tooling
  • Working knowledge of SQL and NoSQL database systems
  • Understanding of security best practices, including identity and access management, encryption, and secure API design
  • Experience using AI agents or AI-enabled tools within software development workflows
  • Experience delivering complex software systems successfully to customers
  • Strong written and verbal communication skills, with the ability to explain technical concepts clearly in English
  • Experience working with remote and geographically dispersed teams across multiple time zones
  • Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, or a related field, or equivalent practical experience
  • Cloud certifications (e.g., AWS Certified Developer, Solutions Architect, or DevOps Engineer) are considered an advantage or
  • Experience in machine learning, data engineering, building AI-enabled applications is desirable
  • Work flexible, Central time business hours


Open to all remote work locations in Canada, USA, and Ireland.


PulseLearning is an equal opportunity employer. We welcome applications from all qualified candidates. Accommodations are available on request for candidates taking part in any stage of the selection process. Please contact hr@pulselearning.com and we will work with you to meet your needs.

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