Work Location: Toronto, Ontario, Canada Hours: 37.5 Line of Business: Analytics, Insights, & Artificial Intelligence Pay Details: $125,500 - $154,000 CAD The 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: We're looking for a highly motivated Applied Machine Learning Scientist II to join our AI2 team. In this role, you'll apply expertise across the end-to-end AI and machine learning lifecycle, including model development, evaluation, testing, validation, deployment, and monitoring for both traditional machine learning and Generative AI solutions. You'll work closely with business, technology, risk, governance, and implementation partners to bring AI capabilities to life and deliver measurable business impact. This role offers an excellent opportunity to combine hands-on machine learning expertise with broader responsibilities related to AI solution assessment, vendor model evaluation, implementation, and governance. You will be expected to work with multiple business partners to advance the use of Machine Learning and AI at TD while supporting the responsible adoption of both internally developed and third-party AI solutions. Key Accountabilities Develop, deploy,



and maintain Predictive and Generative AI solutions for use cases such as Agentic AI, LLM-based models, Pricing, and Anomaly Detection. Lead the evaluation, implementation, testing, monitoring, and ongoing lifecycle management of both internally developed and third-party AI/ML solutions. Assess vendor-provided and out-of-the-box AI models, including their capabilities, limitations, performance characteristics, implementation considerations, and governance implications. Translate business problems into analytical frameworks and collaborate with cross-functional teams to define success metrics, testing methodologies, and solution approaches. Conduct rigorous model evaluation, documentation, A/B testing, validation support, and monitoring to ensure model performance, fairness, stability, and compliance with Responsible AI principles. Communicate complex technical results to technical and non-technical stakeholders and provide actionable recommendations regarding model performance, implementation, and risk. Job Requirements Communication & Relationship Skills Excellent written and verbal communication. Comfortable and effective when interacting with a wide range of business partners and stakeholders. Ability to develop and maintain strong internal 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. Capable of quickly identifying drivers of model performance variation, implementation risks, and monitoring concerns. Ability to evaluate internally developed and vendor-provided AI solutions while balancing business value, performance, and governance requirements. Technical Competencies Proficiency in Python and modern machine learning frameworks and tools. Experience developing, evaluating, and deploying machine learning and Generative AI solutions. Robust understanding of model evaluation methodologies, experimentation, statistical testing, and performance monitoring. Experience with structured and unstructured data, feature engineering, and model interpretability techniques. Exposure to LLMs, agentic AI systems, and practical Generative AI applications. Familiarity with model governance, Responsible AI principles, model validation, and model risk management practices. 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. 5+ years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields. Nice to Have Experience working in financial services or regulated environments. Familiarity with model validation, model risk management, governance, or audit processes. Experience evaluating vendor-provided analytical solutions, AI platforms, or commercial Generative AI products. Familiarity with causal inference, anomaly detection, or agentic AI systems. Who We Are TD is one of the world's leading global financial institutions and is the fifth largest

📌 Applied Machine Learning Scientist Ii (Toronto)
🏢 Altis Labs
📍 Toronto