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Deep Learning Engineer Jobs in Ontario (NOW HIRING)

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 ...

Research Machine Learning Scientist

Toronto, ON ยท On-site

CA$140K - CA$250K/yr

PhD or Master's degree in Computer Science, Statistics, Mathematics, Engineering or a related field * Strong background in machine learning and deep learning * 2+ years of research experience with ...

Senior GEN AI Engineer

Toronto, ON ยท Hybrid

CA$120K - CA$130K/yr

Our challenge Client Capital Markets is seeking a highly skilled AI Engineer with deep expertise in Generative AI, neural networks, and transfer learning to support the development of an innovative ...

Research Engineer

Toronto, ON ยท On-site +1

CA$122K - CA$215K/yr

You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that ...

Showing results 21-40

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 Sep 5, 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?

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 does a deep learning engineer do?

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 skills and qualifications does a deep learning engineer need?

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.

Are deep learning engineers in demand?

Deep learning engineers are in high demand due to the growth of artificial intelligence and machine learning applications across industries such as technology, healthcare, and finance. They typically require skills in neural networks, programming languages like Python, and frameworks such as TensorFlow or PyTorch, with job opportunities increasing as AI adoption expands.

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:

Infographic showing various Deep Learning Engineer job openings in Ontario as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $169,298 per year, or $81.4 per hour.

Lead, Machine Learning Engineer, GFT

Royal Bank of Canada

Toronto, ON โ€ข On-site

Full-time

Re-posted 17 days ago


Key responsibilities

  • Lead the end-to-end lifecycle of AI/ML initiatives, from ideation and proof of concept to development, deployment, and production support.

  • Work on challenging business problems by leveraging large data sets, translating them into machine learning problems, and applying advanced algorithms to generate business value.

  • Design and implement Generative AI solutions, including RAG systems, LLM-powered agents, and NLP pipelines.


Job description

Job Description

What is the opportunity?

As a Senior Manager, AI and ML, you will be working on solving core business problems in compliance (trade surveillance, managing regulatory insights, etc) by leveraging AI and ML to optimize business processes and facilitate informed decision making. You will get the opportunity to work on cutting-edge technology and complex problems that generate significant value and have a high long-term impact on the bank's growth.

What will you do?

  • Work on challenging business problems by leveraging large RBC data, translating them into machine learning problems and applying advanced machine learning algorithms to generate business value
  • Lead the end-to-end lifecycle of AI/ML initiatives-from ideation and POC through development, deployment, and production support
  • Design and implement Generative AI solutions, including Retrieval-Augmented Generation (RAG) systems, LLM-powered agents, and NLP pipelines
  • Provide technical leadership and mentorship to team members, fostering a culture of innovation and continuous learning
  • Collaborate with engineering, architecture, and model risk management teams to ensure solutions meet enterprise standards for scalability, security, and governance
  • Stay current with emerging AI/ML technologies and evaluate their applicability to Compliance use cases
  • Communicate complex technical concepts to non-technical stakeholders and senior leadership

What do you need to succeed?

Must have:

  • PhD or Masters in a quantitative discipline such as computer science, mathematics, statistics, or engineering
  • Excellent verbal and written communication skills; ability to work collaboratively with cross-functional teams including business, engineering, and risk management
  • 7+ years of expert level programming experience in Python (preferable) and other languages is a must - ability to write production level code and documentation
  • 5+ years' experience working with large unstructured and structured datasets - exploring and understanding data, cleaning and pre-processing, performing exploratory data analysis, generating business insights and communicating them in a clear, concise manner
  • 5+ years' experience developing and deploying models in production for real business problems
  • Knowledge of standard machine learning libraries like numpy, pandas, scikit learn and visualization packages like seaborn or matplotllib, etc and machine learning algorithms like logistic regression, tree based models, decision trees, random forests, etc
  • Strong understanding and work experience with core NLP and Generative AI like embeddings, text pre-processing, RNN's, Transformer architecture, fine-tuning models, prompting techniques, etc
  • Demonstrated experience designing and implementing Retrieval-Augmented Generation (RAG) architectures, including vector databases, embedding models, and retrieval pipelines
  • Experience building and deploying RESTful APIs for ML model serving (FastAPI, Flask)
  • Experience with MLOps practices, model serving, monitoring, and CI/CD pipelines for ML systems
  • Experience working with version control - git and linux.

Nice-to-have:

  • Experience building autonomous AI agents and multi-agent orchestration frameworks (e.g., LangChain, LangGraph, AutoGen)
  • Prior experience in financial services, particularly in Compliance, Risk, or Regulatory Technology
  • Experience working with big data, pyspark, scala
  • Experience working with deep learning - RNN's, Transformer models, etc
  • 2+ years' experience working with Deep Learning Frameworks like Tensorflow or Pytorch

What's in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
  • Leaders who support your development through coaching and managing opportunities
  • Ability to make a difference and lasting impact
  • Work in a dynamic, collaborative, progressive, and high-performing team
  • A world-class training program in financial services
  • Opportunities to do challenging work
  • Opportunities to take on progressively greater accountabilities
  • Opportunities to build close relationships with clients
  • Access to a variety of job opportunities across business and geographies

#LI-Post

#LI- PK

Job Skills

Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)

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:

2026-04-27

Application Deadline:

2026-09-15

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