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Research Assistant Deep Learning Jobs in Ontario

The Capital Markets Data AI and Research Technology (DART) team is looking for a hands-on AI ... Must-have * A PhD or Master's degree in Computer Science, Machine Learning, Deep Learning, or ...

Our research broadly spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and responsible use of AI. We have access to massive financial ...

Research Scientist, Simulation Agents

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. ... Qualifications: - Masters/PhD in machine learning, computer science, engineering, or a related ...

Research Scientist

Toronto, ON · On-site

CA$158K - CA$269K/yr

Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. ... Qualifications: - Masters/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ...

Showing results 41-60

Research Assistant Deep Learning information

What is a research assistant deep learning?

Research Assistant Deep Learning jobs involve supporting research projects focused on artificial intelligence, specifically within the field of deep learning. These roles typically require assisting with data collection, preprocessing, running machine learning experiments, and analyzing results. Research assistants may also help with literature reviews, code development, and documentation. The position is often found in academic, industry, or research lab settings, and usually requires a solid foundation in programming, mathematics, and neural network concepts.

What does a research assistant deep learning do?

As a Research Assistant in Deep Learning, you can expect to work closely with research scientists and engineers to design, implement, and evaluate novel deep learning models. Typical daily tasks include data preprocessing, running experiments, analyzing results, and contributing to academic papers or presentations. You may also assist in developing codebases, conducting literature reviews, and collaborating with team members to solve technical challenges. The work environment is often collaborative and fast-paced, with opportunities to learn from experts and contribute to cutting-edge research projects.

What are the key skills and qualifications needed to thrive as a research assistant deep learning?

To thrive as a Research Assistant in Deep Learning, you need a strong background in machine learning, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience with data preprocessing and GPU computing, are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are essential for efficiently developing, testing, and improving advanced machine learning models in a fast-evolving field.

What is the difference between Research Assistant Deep Learning vs Research Assistant Machine Learning?

AspectResearch Assistant Deep LearningResearch Assistant Machine Learning
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, Data Science, or related fields; foundational ML knowledge
Work EnvironmentResearch labs, universities, tech companies focusing on AI and neural networksResearch labs, universities, tech companies working on various ML algorithms
Employer & Industry UsageAI research, deep learning projects, neural network developmentGeneral machine learning applications, data analysis, predictive modeling

Research Assistant Deep Learning specializes in neural networks and AI-focused projects, while Research Assistant Machine Learning covers a broader range of algorithms and data analysis tasks. Both roles require similar educational backgrounds but differ in technical focus and application areas.

What are popular job titles related to Research Assistant Deep Learning jobs in Ontario?

For Research Assistant Deep Learning jobs in Ontario, the most frequently searched job titles are:

What cities in Ontario are hiring for Research Assistant Deep Learning jobs?

Cities in Ontario with the most Research Assistant Deep Learning job openings:

Infographic showing various Research Assistant Deep Learning job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Software Engineer

Royal Bank of Canada

Toronto, ON • On-site

Full-time

Re-posted 26 days ago


Job description

Job Description


What's the opportunity?

RBC Borealis is 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, 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:

  • 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?

  • Be part of a dynamic & flexible working environment;

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

  • 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 the AI Group

RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people. In addition to helping scale the biggest AI opportunities at RBC, the AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations. The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery - ensuring RBC remains at the frontier of AI-enabled value creation.

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.

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.

#Ll-POST

#TechPJ

Job Skills

Big Data Analytics, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Software Engineering, Software Product Design

Additional Job Details

Address:

777 BAY ST, TH 27:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

HUMAN RESOURCES & BMCC

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-07-27

Application Deadline:

2026-09-30

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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Employment Type: FULL_TIME