Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
About the role
- Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
Responsibilities
- Develop, deploy, and maintain Generative AI and predictive machine learning solutions
- Work on use cases including customer and employee assistance, claims and underwriting support, operational automation, and risk assessment
- Lead evaluation, implementation, testing, monitoring, and lifecycle management of internally developed and third-party AI/ML solutions
- Assess vendor-provided and out-of-the-box AI models for capabilities, limitations, performance, implementation considerations, and governance implications
- Translate business problems into analytical frameworks
- Collaborate with business, technology, risk, governance, and implementation partners
- Define success metrics, testing methodologies, and solution approaches
- Conduct model evaluation, documentation, A/B testing, validation support, and monitoring
- Ensure model performance, fairness, stability, and compliance with Responsible AI principles
- Communicate technical results to technical and non-technical stakeholders
- Provide actionable recommendations on model performance, implementation, and risk
- Support responsible adoption of internally developed and third-party AI solutions
Requirements
- Undergraduate degree in Science, Technology, Engineering, Mathematics, Economics, Finance, or a related quantitative discipline
- 5+ years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields
- Excellent written and verbal communication skills
- Ability to interact effectively with business partners and stakeholders
- Ability to translate complex technical concepts and analytical findings into clear business language
- Strong conceptual and problem-solving skills
- Proficiency 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 LangGraph
- Ability to design stateful, multi-step agent workflows using deterministic logic, LLM 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
- Graduate degree is considered an asset
- For Quebec roles: maîtrise d’une langue autre que le français to support or deal with employees or colleagues requiring services in a language other than French
Benefits
- Base salary
- Variable compensation
- Health and well-being benefits
- Savings and retirement programs
- Paid time off
- Banking benefits and discounts
- Career development opportunities
- Reward and recognition programs
- Regular development conversations
- Training programs
- Online learning platform
- Mentoring programs
- Training and onboarding sessions
- Interview accommodations, including accessible meeting rooms and captioning for virtual interviews
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