Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
About the role
- 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.
Responsibilities
- Develop, deploy, and maintain Generative AI and predictive machine learning solutions for customer and employee assistance, claims and underwriting support, operational automation, and risk assessment
- Evaluate, implement, test, monitor, and manage the ongoing lifecycle of internally developed and third-party AI/ML solutions
- Assess vendor-provided and out-of-the-box AI models, including capabilities, limitations, performance, implementation considerations, and governance implications
- Translate well-defined business problems into analytical frameworks
- Collaborate with cross-functional teams to define success metrics, testing methodologies, and solution approaches
- Contribute to model evaluation, documentation, A/B testing, validation support, and monitoring
- Help ensure model performance, fairness, stability, and compliance with Responsible AI principles
- Communicate technical results to technical and non-technical stakeholders
- Contribute to recommendations regarding model performance, implementation, and risk
- Support responsible adoption of internally developed and third-party AI solutions
Requirements
- Excellent written and verbal communication skills
- Ability to collaborate with business, technology, risk, and governance stakeholders
- Strong conceptual and problem-solving skills
- Proficiency in Python and modern machine learning frameworks and tools
- Practical experience developing or evaluating machine learning or Generative AI solutions through professional work, internships, research, or substantial academic or personal projects
- Understanding of model evaluation methodologies, experimentation, statistical testing, and performance monitoring
- Familiarity with structured and unstructured data, feature engineering, and model interpretability techniques
- Exposure to LLMs, agentic AI systems, and practical Generative AI applications
- Familiarity with agent orchestration frameworks such as LangGraph
- Understanding of stateful, multi-step agent workflows involving deterministic logic, LLM-driven reasoning, tool calling, conditional routing, memory, or human-in-the-loop controls
- Exposure to integrating LLM applications with APIs, retrieval-augmented generation pipelines, vector stores, structured outputs, or external tools and data sources
- Familiarity with production practices for Generative AI systems, including prompt and workflow versioning, automated evaluation, tracing, observability, guardrails, retry and fallback strategies, and latency and cost considerations
- Familiarity with model governance, Responsible AI principles, model validation, or model risk management practices is an asset
- Experience with SQL, Azure Cloud, Azure ML Services, or Databricks is an asset
- Undergraduate degree in Science, Technology, Engineering, Mathematics, Economics, Finance, or a related quantitative discipline
- 1–3 years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields
- Relevant internships, research, co-op placements, and substantial academic or personal projects may be considered
- For Quebec roles: maîtrise d’une langue autre que le français pour offrir du soutien ou traiter avec des employés ou des collègues qui ont besoin de services et de soutien dans une langue autre que le français
Benefits
- Base salary and variable compensation
- Health and well-being benefits
- Savings and retirement programs
- Paid time off
- Banking benefits and discounts
- Career development
- Reward and recognition programs
- Regular development conversations, training programs, and online learning platform
- Mentoring programs
- Training and onboarding sessions
- Interview accommodations, including accessible meeting rooms and captioning for virtual interviews
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