Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Target Resume Now
Tailor your resume to this Technical Product Owner, AI & Machine Learning Solutions role.
Rezi rewrites your resume against TD's job description. Free.
Tailor your resume to this Technical Product Owner, AI & Machine Learning Solutions role.
Rezi rewrites your resume against TD's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Technical Product Owner, AI & Machine Learning Solutions posting at TD — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Technical Product Owner, AI & Machine Learning Solutions posting at TD — free, in seconds.
About the Role
Layer 6 is the AI research center of excellence for TD Bank Group, developing and deploying industry-leading machine learning systems. This highly technical role focuses on delivering AI, Machine Learning, and Generative AI solutions, requiring hands-on experience and the ability to evaluate technical designs and drive delivery outcomes.
Responsibilities
- Lead cross-functional teams of machine learning scientists, machine learning engineers, data scientists and software engineers to deliver production-grade AI solutions.
- Work closely with stakeholders to identify, refine and occasionally reject opportunities to build machine learning products; collaborate with support functions such as risk, technology, model risk management and incorporate interfacing features.
- Translate business objectives into technically feasible AI/ML solutions and articulate trade-offs related to architecture, implementation complexity, scalability, risk, and model performance.
- Develop the vision, strategy, and roadmap for AI technical products and capabilities that meet business objectives and maintain TD at the forefront of AI research and development.
- Maintain an in-depth understanding of the solution, architecture, and technical implementation details to effectively challenge design decisions, assess delivery trade-offs, and prioritize development work in alignment with business and technical requirements.
- Facilitate the professional and technical development of colleagues through mentorship and feedback.
- Anticipate resource needs as solutions move through the model lifecycle, scaling pods up and down as models are built, perform, degrade and require enhancement.
- Establish and uphold AI/ML engineering standards, best practices, and quality controls, while providing informed challenge on model design, MLOps, data architecture, and production-readiness decisions.
- Lead the definition of cloud-native AI/ML solution architectures and operational strategies, partnering with engineering and architecture teams to ensure scalable deployment, monitoring, and lifecycle management of production AI systems.
- Ensure AI solutions meet enterprise standards for security, governance, model risk management, responsible AI, compliance, operational resilience, and auditability.
- Define, measure, and communicate the business value delivered by your products, connecting model performance to measurable business outcomes and enterprise AI value targets.
Requirements
- 5+ years of experience delivering complex AI, machine learning, data science, advanced analytics, or software products in large-scale enterprise environments.
- 3+ years of experience leading cross-functional technical delivery teams consisting of machine learning engineers, data scientists, software engineers, and MLOps practitioners.
- Ability to evaluate technical designs and challenge architecture decisions while partnering effectively with engineering and research teams.
- Familiarity with model risk management and AI governance in regulated industries.
Skills
- Deep understanding of machine learning, generative AI, large language models, retrieval systems, model evaluation techniques, data engineering, MLOps, and software development practices.
- Strong technical proficiency in Python, SQL, and modern software engineering practices including version control, CI/CD, automated testing, observability, and deployment automation.
Location
- Toronto, Ontario, Canada
Work Type
- Full-time
Experience Level
- II
Education Level
- Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, or a related technical field; or equivalent practical experience delivering complex AI/ML solutions.
Salary/Compensations
- $115,000 - $145,000 CAD
Benefits
- Health and well-being benefits
- Savings and retirement programs
- Paid time off
- Banking benefits and discounts
- Career development
- Reward and recognition programs
- Training programs
- Competitive benefits plan
About the Company
- TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores.
- Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world.
- More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience.
- TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing.
- Together, we are reimagining what banking can be for our clients, colleagues and communities.
Equal Opportunity
- We're committed to providing the support our colleagues need to thrive both at work and at home.
- We hire and develop the best.
- We foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals.