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Artificial Intelligence Machine Learning Engineer Jobs in Toronto, ON

As a Machine Learning Engineer Lead, you will join our Data Science & AI Pod, focused on designing, building, and deploying enterprise-wide AI and machine learning solutions that support business ...

We are searching for a season AI Systems Architecture Engineer to be part of the Qualcomm AI Processor team responsible for analyzing and developing Artificial Intelligence / Machine Learning ...

Senior Machine Learning Engineer

Toronto, ON Β· On-site

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning ... BDO may use artificial intelligence enabled tools to support certain aspects of the recruitment ...

Advanced programming skills in Python, with practical experience using popular machine learning ... BDO may use artificial intelligence enabled tools to support certain aspects of the recruitment ...

What you'll do As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to ...

Lead Machine Learning Engineer

Toronto, ON Β· Remote

$225K - $260K/yr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

Showing results 21-40

Artificial Intelligence Machine Learning Engineer information

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON?

For Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Toronto, ON with the most Artificial Intelligence Machine Learning Engineer job openings:

Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Toronto, ON as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 76% Full Time, 20% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Applied Machine Learning Scientist II (ATH # 5215)

Toronto, ON β€’ On-site

CA$125K - CA$154K/yr

Full-time

Re-posted 7 days 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.