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Deep Learning Engineer Jobs in Ontario (NOW HIRING)

As aPrincipal Machine Learning Engineer, you will operate at the intersection of AEC data, machine ... This role goes beyond traditional model development; you will dive deep into complex design and ...

... deep learning, machine learning, natural language processing, and big data. Responsibilities ... Work closely with machine learning engineers and data scientists to design, build, and test models.

Founded by a team with deep retail and retail-technology experience, Thri5 is venture-backed by some of Canada's most prominent VC and angel investors. Your Role As an AI / Machine Learning Engineer ...

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and ... and deep learning, with a proven track record of building, hosting, and deploying ML models on ...

Machine Learning Engineering Manager

Toronto, ON ยท On-site

CA$148K - CA$266K/yr

... learning engineering or related field * 3+ years of experience as a manager * Experience building ... Experience training deep neural nets, such as CNN and transformers and proficiency in least one ...

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Deep Learning Engineer information

See Ontario salary details

$90.5K

$169.3K

$228K

How much do deep learning engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for deep learning engineer in Ontario is $169,298.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,500.00 and $188,000.00 per year, depending on experience, location, and employer.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

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

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What are popular job titles related to Deep Learning Engineer jobs in Ontario? For Deep Learning Engineer jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Deep Learning Engineer jobs in Ontario look for? The top searched job categories for Deep Learning Engineer jobs in Ontario are:
Infographic showing various Deep Learning Engineer job openings in Ontario as of June 2026, with employment types broken down into 10% Internship, 70% Full Time, and 20% Contract. Highlights an 96% In-person, and 4% Hybrid job distribution, with an average salary of $169,298 per year, or $81.4 per hour.
Machine Learning Software Engineer II

Machine Learning Software Engineer II

Royal Bank of Canada

Toronto, ON โ€ข On-site

Full-time

Posted 25 days ago


Job description

Job Description

What's the opportunity?

We're looking for an enthusiastic software developer who's excited by the opportunity of working on challenging problems at the intersection of machine learning and the financial services industry. As a Machine Learning Software Engineer II, you'll be responsible for owning and delivering a project end to end - everything from data pre-processing and exploration, to building and scaling ML algorithms and pipelines, to deployment and monitoring of production systems. 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 cutting-edge machine learning R&D.

Your responsibilities include:

  • To build cutting edge ML solutions throughout the research and product development lifecycle;

  • To play a key role in the design and development of Borealis' machine learning products;

  • To partner with RBC Borealis's research and product teams to ensure the seamless delivery of these products;

  • To apply engineering and data best practices to build robust and scalable large-scale machine learning software systems;

  • To support projects with thorough documentation, design decisions, and technical advisory.

You're our ideal candidate if you have:

  • A degree in Computer Science, Software Engineering, or equivalent field;

  • 5+ years of experience as a software engineer;

  • Experience building modular and robust software systems in Python or similar language;

  • Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews and source control management;

  • Experience working across the entire ML research and product lifecycle from prototyping to production is a plus;

  • Experience building microservices, data pipelines and using relational and non-relational databases is a plus;

  • Experience working with data science tooling and deep learning frameworks is a plus;

  • Experience with DevOps engineering (CI/CD pipelines, observability, containers etc) is a plus.

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, an RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo, and Vancouver, we support academic collaborations and partner with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.

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.

Job Skills

Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages

Additional Job Details

Address:

777 BAY ST, TH 27: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:

2026-03-17

Application Deadline:

2026-10-05

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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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