Applied Machine Learning Scientist I

Posted 13 Days Ago
Be an Early Applicant
Toronto, ON, CAN
In-Office
106K-125K Annually
Junior
Fintech • Insurance • Financial Services
The Role
Design, build, and deploy predictive and generative ML models (including LLMs) for banking use cases. Create production-ready, modular ML pipelines, evaluate and monitor models, run A/B tests, and translate business problems into measurable solutions while collaborating cross-functionally.
Summary Generated by Built In

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:

Additional Job Description

We’re looking for a highly motivated Applied Machine Learning Scientist to join our AI2 team. In this role, you’ll drive the development and deployment of ML solutions that power data-driven decision-making across our Canadian Personal Banking division. You’ll work closely with various teams to bring AI capabilities to life and deliver measurable business impact.

This is a unique opportunity work on high-impact initiatives in a fast-growing function. If you're passionate about solving real-world problems with machine learning and want to make a tangible difference at scale, we'd love to hear from you.

What You’ll Do

  • Develop, deploy, and maintain Predictive and Generative AI models for use cases such as Agentic AI, Chatbots, Pricing, and Anomaly Detection, Forecasting

  • Design and implement clean, modular, and reusable ML codebases using object-oriented programming (OOP) principles and best coding practices

  • Translate business problems into analytical frameworks and collaborate with cross-functional teams to define success metrics and solution approaches

  • Build production-ready ML pipelines, ensuring robustness, scalability, and maintainability

  • Conduct rigorous model evaluation, documentation, A/B testing, and monitoring to ensure model performance, fairness, and stability in production

  • Communicate complex technical results to non-technical stakeholders and provide actionable insights

  • Stay current with ML research, GenAI advancements, and software engineering best practices to bring innovative approaches into production

What You Bring

  • 2+ years of experience applying machine learning to real-world business problems

  • Strong proficiency in Python for ML modeling and implementation

  • Experience building maintainable, well-tested, and production-quality ML code

  • Proficiency with key ML libraries and frameworks

  • Experience working with structured and unstructured data, feature engineering, and model interpretability techniques

  • Exposure to GenAI or large language models and their practical applications

  • Hands-on experience with model deployment, monitoring, and lifecycle management in production environments

  • Strong problem-solving skills and a track record of delivering results in cross-functional teams

  • Undergraduate degree required; advanced technical degree in a STEM field preferred

Nice to Have

  • Experience working in financial services or regulated environments

  • Familiarity with causal inference, anomaly detection, or agent-based systems

  • Experience applying software engineering practices such as code reviews, version control, testing, and documentation in ML projects

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):

Sans Objet

Skills Required

  • 2+ years applying machine learning to real-world business problems
  • Proficiency in Python for ML modeling and implementation
  • Experience building maintainable, well-tested, production-quality ML code
  • Proficiency with key ML libraries and frameworks
  • Experience with structured and unstructured data, feature engineering, and model interpretability
  • Exposure to Generative AI or large language models and their applications
  • Hands-on experience with model deployment, monitoring, and lifecycle management in production
  • Undergraduate degree in a relevant field (advanced STEM degree preferred)
  • Experience in financial services or regulated environments
  • Familiarity with causal inference, anomaly detection, or agent-based systems
  • Experience applying software engineering practices (code reviews, version control, testing, documentation) in ML projects

TD Bank Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about TD Bank and has not been reviewed or approved by TD Bank.

  • Parental & Family Support Parental and family-building support is positioned as a standout, including 16 weeks of paid parental leave for all parents and assistance for fertility, surrogacy, donor support, adoption, and doula reimbursement. This breadth is framed as above average for large U.S. employers and notable within banking.
  • Retirement Support Retirement support is presented as robust, with 401(k) and employer funding described in detail in some summaries (fixed contribution plus additional matching) alongside other savings programs. Employee banking discounts and related financial perks add to the overall rewards value beyond salary.
  • Healthcare Strength Healthcare and mental well-being benefits are characterized as comprehensive, including multiple medical plan options, virtual care, and an Employee & Family Assistance Program with continuous access. These elements are repeatedly emphasized as core components of the Total Rewards offering.

TD Bank Insights

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The Company
HQ: Pearl River, NY
93,823 Employees
Year Founded: 1955

What We Do

The Toronto-Dominion Bank & its subsidiaries are collectively known as TD Bank Group (TD). TD is the sixth largest bank in North America by branches & serves approximately 22 million customers in a number of locations in key financial centres around the globe. Over 85,000 TD employees represent the strongest team in banking. Delivering legendary customer experiences is who we are & is part of being the Better Bank. Visit our Careers page to learn more about TD & why TD is a great place to work.

Why Work With Us

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