Work Location:Toronto, Ontario, CanadaHours:37.5Line of Business:Analytics, Insights, & Artificial IntelligencePay Details:125,500 - 154,000 CADTD 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:Job Description:We're looking for a highly motivated and experienced Applied Machine Learning Scientist II 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 take ownership 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 work closely with business, technology, risk, governance, and implementation partners to shape solution direction, influence decisions, and bring AI capabilities to life with 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 AI and Machine Learning at TDI while supporting the responsible adoption of both internally developed and third-party AI solutions.KEY ACCOUNTABILITIESDevelop, deploy,



and maintain 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.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 REQUIREMENTSCommunication & Relationship SkillsExcellent written and verbal communication skills.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 transparent business language.Strategic Thinking & JudgmentCreative,



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 CompetenciesProficiency in Python and modern machine learning frameworks and tools.Experience developing, evaluating, and deploying machine learning and Generative AI solutions.Strong 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.Hands-on experience with agent orchestration frameworks such as LangGraphAbility to design stateful, multi-step agent workflows that combine deterministic logic with LLM-driven reasoning, tool calling, conditional routing, memory, and human-in-the-loop controls.Experience integrating LLM applications with enterprise APIs, retrieval-augmented generation pipelines, vector stores, structured outputs, and external tools or data sources.Knowledge of production engineering practices for Generative AI systems, including prompt and workflow versioning, automated evaluation, tracing, observability, guardrails, retry and fallback strategies, and latency and cost optimization.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 & ExperienceUndergraduate 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.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)
🏢 TD
📍 Toronto