Applied Machine Learning Scientist I

TD • Toronto, ON

18d

About The Position

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.

Requirements

• 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 Haves

• 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

Responsibilities

• 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

Benefits

• 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.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 101-250 employees