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Applied Machine Learning Scientist I

Toronto, ON, Canada
Montreal, QC, Canada

Job type: Full-time
Apply by: Oct 23, 2026
Experience: 1–3 years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields.
Posting language: English
Posted: Sep 22, 2026

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Original job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

105,500 - 125,000 CAD

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:

We're looking for a highly motivated Applied Machine Learning Scientist I to join our TDI AI/ML team. This role is primarily focused on Generative AI, including LLM-based and agentic solutions, while also offering opportunities to work on predictive machine learning use cases. You'll contribute across the end-to-end AI and machine learning lifecycle, including solution design, model development, evaluation, testing, validation, deployment, monitoring, and continuous improvement. You'll collaborate with business, technology, risk, governance, and implementation partners to help bring AI capabilities to life with measurable business impact.

This role offers an excellent opportunity to build hands-on machine learning expertise while gaining exposure to AI solution assessment, vendor model evaluation, implementation, and governance. You will work with business partners and experienced colleagues to advance the use of AI and Machine Learning at TDI while supporting the responsible adoption of both internally developed and third-party AI solutions.

KEY ACCOUNTABILITIES

Contribute to the development, deployment, and maintenance of Generative AI and predictive machine learning solutions for use cases such as customer and employee assistance, claims and underwriting support, operational automation, and risk assessment.
Support the evaluation, implementation, testing, monitoring, and ongoing lifecycle management of both internally developed and third-party AI/ML solutions.
Assist in assessing vendor-provided and out-of-the-box AI models, including their capabilities, limitations, performance characteristics, implementation considerations, and governance implications.
Help translate well-defined business problems into analytical frameworks and collaborate with cross-functional teams to define success metrics, testing methodologies, and solution approaches.
Contribute to model evaluation, documentation, A/B testing, validation support, and monitoring to help ensure model performance, fairness, stability, and compliance with Responsible AI principles.
Communicate technical results clearly to technical and non-technical stakeholders and contribute to recommendations regarding model performance, implementation, and risk.

JOB REQUIREMENTS

Communication & Relationship Skills

Excellent written and verbal communication skills.
Comfortable collaborating with a range of business partners and stakeholders, with a willingness to develop these skills further.
Ability to build positive working relationships across business, technology, risk, and governance functions.
Ability to translate complex technical concepts and analytical findings into clear business language.

Strategic Thinking & Judgment

Creative, out-of-the-box thinker with strong conceptual and problem-solving skills.
Motivated to constantly identify innovative ways to enhance analytical solutions and AI implementation practices.
Ability to investigate drivers of model performance variation and identify potential implementation or monitoring concerns with guidance.
Interest in evaluating internally developed and vendor-provided AI solutions while considering business value, performance, and governance requirements.

Technical Competencies

Proficiency in Python and modern machine learning frameworks and tools.
Practical experience developing or evaluating machine learning or Generative AI solutions through professional work, internships, research, or substantial academic or personal projects.
Understanding of model evaluation methodologies, experimentation, statistical testing, and performance monitoring.
Familiarity with structured and unstructured data, feature engineering, and model interpretability techniques.
Exposure to LLMs, agentic AI systems, and practical Generative AI applications.
Familiarity with agent orchestration frameworks such as LangGraph, gained through work, research, coursework, or personal projects.
Understanding of stateful, multi-step agent workflows involving deterministic logic, LLM-driven reasoning, tool calling, conditional routing, memory, or human-in-the-loop controls.
Exposure to integrating LLM applications with APIs, retrieval-augmented generation pipelines, vector stores, structured outputs, or external tools and data sources.
Familiarity with production practices for Generative AI systems, such as prompt and workflow versioning, automated evaluation, tracing, observability, guardrails, retry and fallback strategies, or latency and cost considerations.
Familiarity with model governance, Responsible AI principles, model validation, or model risk management practices is an asset.
Experience with SQL, Azure Cloud, Azure ML Services, or Databricks is an asset.

Education & Experience

Undergraduate degree in Science, Technology, Engineering, Mathematics, Economics, Finance, or a related quantitative discipline.
Graduate degree is considered an asset.
1–3 years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields. Relevant internships, research, co-op placements, and substantial academic or personal projects may be considered.

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):

Maîtrise d’une langue autre que le français pour offrir du soutien ou traiter avec des employés ou des collègues qui ont besoin de services et de soutien dans une langue autre que le français.

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More about this job

Responsibilities

You will contribute to the end-to-end lifecycle of Generative AI and predictive machine learning solutions, including design, development, deployment, and monitoring. You will also collaborate with cross-functional partners to translate business problems into analytical frameworks and ensure responsible AI adoption.

Requirements

The role requires an undergraduate degree in a quantitative discipline and 1-3 years of relevant experience in machine learning or data science. Proficiency in Python and familiarity with modern machine learning frameworks, LLMs, and agentic workflows are essential.

Skills

Python
Machine learning
Generative AI
LLM
Agentic AI
SQL
Azure Cloud
Azure ML Services
Databricks
Model evaluation
Statistical testing
Feature engineering
Model interpretability
LangGraph
Retrieval-augmented generation
Model governance

Benefits

Health and well-being benefits
Savings and retirement programs
Paid time off
Banking benefits and discounts
Career development
Reward and recognition programs

Visa sponsorship

Not detected in the job text

Keywords

Applied Machine Learning
Generative AI
LLM
Agentic AI
Python
SQL
Azure Cloud
Azure ML Services
Databricks
LangGraph
Predictive Modeling
Model Governance
Responsible AI
Retrieval-Augmented Generation
Feature Engineering
Model Validation
A/B Testing
Data Science
Analytics
Artificial Intelligence
Risk Assessment
Operational Automation
Model Monitoring
Statistical Testing
Agent Orchestration
Vector Stores
Observability
Guardrails
Quantitative Analysis
Financial Services

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