Applied Machine Learning Scientist II
Analytics, Insights, & Artificial Intelligence
Work LocationToronto, Ontario, Canada
Hours37.5
Line Of BusinessAnalytics, Insights, & Artificial Intelligence
Pay Details125, CAD
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 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.
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Job DescriptionWe'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 Accountabilities- Develop, 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.
- Excellent 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 clear business language.
- Creative, out-of-the-box thinker with strong conceptual and problem-solving skills.
- Motivated to constantly identify innovative ways…
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