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Research Assistant Deep Learning Jobs in Ontario

Waabi

Research Scientist, Learnable Planner

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

You will... - Design and execute on a research agenda for deep-learning based motion planning for ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Our work spans the field of machine learning with areas such as deep learning and generative AI ... We are driven to be at the cutting edge of machine learning in research, engineering, and impactful ...

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Machine learning, natural language processing, learning-to-rank, online learning, deep learning ... Research and development on cutting-edge machine learning technologies. Qualifications and Skills:

Waabi

Senior / Staff Perception Engineer

Toronto, ON · On-site

CA$158K - CA$269K/yr

... research insights, leveraging your expertise in deep learning, computer vision, and self-driving ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

OpenSpace

Sr. Computer Vision Engineer

Toronto, ON

CA$168K - CA$220K/yr

You will leverage classical CV, deep learning (transformers, multi-modal models), and probabilistic ... Collaborate with platform engineers to transition research prototypes into production-ready ...

Future Education

£85 - £100/day

Learning Support Assistants (Merton) Are you passionate about making a difference in students ... Future Education, established by experienced educators with a deep understanding of the education ...

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All JobsResearch Deep Learning JobsResearch Assistant Deep Learning JobsResearch Assistant Deep Learning Jobs in Ontario

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 job categories do people searching Research Assistant Deep Learning jobs in Ontario look for?

The top searched job categories for Research Assistant Deep Learning jobs in Ontario 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:

Research Assistant Deep Learning jobs near you
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.

Applied Machine Learning Scientist II (ATH # 5215)

Td

Toronto, ON

CA$125K - CA$154K/yr

Full-time

Re-posted 17 hours ago

Key responsibilities

  • Validate, review, and test Generative AI and Deep Learning models, providing effective challenge and assessment.

  • Conduct research and development in Generative AI, Agentic AI, and Large Language Model evaluation, testing, and explainability.

  • Communicate findings and recommendations to technical and non-technical stakeholders.

Job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$125,500 - $154,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

*Department Overview

TD Model Validation (MV) group is responsible for the independent validation and approval of models used forAgentic AI,Generative AI, Natural Language Processing (NLP), credit, fraud, and marketing models. The Artificial Intelligence/Machine Learning (AI/ML) MV team is responsible for the validation of all AI/ML models used across the Bank for various use cases.

*Job Description

The position reports to SeniorApplied Machine Learning Scientist(Generative AI),inthe AI/ML Model Validation team and is primarily focused on the validation and review of Generative AI and Deep Learning models.

Detailed accountabilities include:

  • Validate (review, test, and provide effective challenge) AI/ML models, particularly Generative AI and Deep Learning models.

  • Conduct R&Din the area ofGenAI / Agentic AI / LLM evaluation, testing, explainability.

  • Stay up to date with advancements in the field of Generative AI including major publications, important Large Language Models (LLMs), evaluation metrics, technology stacks, and datasets.

  • Maintain full professional knowledge of techniques and developments in the field of AI/ML and share knowledge with business partners and senior management.

  • Develop/implement AI/ML model validation methodologies and standards. Ensure that the validation methodologies and standards are in line withindustrybest practices and address regulatory and audit requirements.

  • Develop and apply a variety of statistical tests and modeling techniques to identify/recommend improvements to models and undertake related initiatives. Implement benchmark models as applicable.

  • Communicate findings and recommendations to both technical and non-technical stakeholders.

The position involves working effectively with different internal partners suchas AI2, Layer6, P&T, and FCRM.

*Job Requirements

  • Strong quantitative skills with an advanced degree in one or more of the following areas: computer science, machine learning, engineering, statistics, mathematics, or physics.

  • Proven experience as Generative AI Scientist, Machine Leaning Scientist, or a similar role.

  • Ability to work independently and collaboratively in a fast-paced, dynamic environment. Great time management and multitasking skills with minimal supervision.

  • Experience with and strong knowledge of AI/ML methodologies including Generative AI, Agentic AI, Deep Learning, modern Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Transformers, Diffusion models

  • Experience with Deep Learning and Generative AI technology stacks and libraries such asPyTorch,LangChain,HuggingFace,PromptFlow, etc.

  • Motivated to stay up to date with the latest advancements in Generative AI, Prompt Engineering, Machine Learning, and Cloud technologies.

  • Proficient in scripting/programming language-Python.

  • Familiarity with cloud platforms (e.g., Azure, AWS).

  • Familiarity with Data Structures, Algorithm design, and principles of Object-Oriented Programming (OOP).

  • Knowledge of machine learning explain-ability/interpretability algorithms.

  • Excellent verbal and written communication skills. The position requires writing clean technical reports.

* Nice to have qualifications

  • Publications in the relevant conference and journalsisa plus.

  • Ability to implement AI/ML algorithms from academic research papers is a plus.

  • Knowledge of SQL and database systems.

Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We're delighted that you're considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we're committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.


Colleague Development

If you're interested in a specific career path or are looking to build certain skills, we want to help you succeed. You'll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you're passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you've got everything you need to succeed in your new role.

Interview Process
We'll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.


Accommodation
Your accessibility is important to us. Please let us know if you'd like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.
We look forward to hearing from you!

Language Requirement (Quebec only):

Ce poste n'exige pas la maitrise d'une langue autre que le francais.

Apply