Technical Product Owner, AI & Machine Learning Solutions

🔥 0 minutes ago

🇨🇦 Canada – Remote

💵 $115k - $145k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

⚒️ Technical Product Manager (TPM)

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TD

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1855

🏦 Banking

💸 Finance

🛡️ Insurance

💰 Grant on 2023-10

Banking • Finance • Insurance

TD is one of North America's biggest banks offering a wide range of banking services including personal and business banking, insurance, wealth management, and securities. TD is committed to sustainability, diversity, equity, and inclusion, ensuring a supportive and inclusive workplace where employees are empowered to grow. The bank provides various roles and career opportunities across different regions with a focus on community impact and professional development. TD's culture is defined by care and respect, aimed at benefiting their business performance, customers, and communities.

📋 Description

• Lead cross-functional teams of machine learning scientists, machine learning engineers, data scientists, and software engineers to deliver production-grade AI solutions • Work with stakeholders to identify, refine, and occasionally reject machine learning product opportunities • Collaborate with risk, technology, model risk management, and other support functions • Translate business objectives into technically feasible AI/ML solutions and articulate architecture, implementation, scalability, risk, and model-performance trade-offs • Develop the vision, strategy, and roadmap for AI technical products and capabilities • Maintain detailed understanding of solutions, architectures, and technical implementations to challenge design decisions and prioritize development • Facilitate colleagues’ professional and technical development through mentorship and feedback • Anticipate resource needs throughout the model lifecycle and scale pods as needed • Establish AI/ML engineering standards, best practices, and quality controls • Provide informed challenge on model design, MLOps, data architecture, and production-readiness decisions • Lead cloud-native AI/ML solution architecture and operational strategy definition • Partner with engineering and architecture teams on scalable deployment, monitoring, and lifecycle management of production AI systems • Ensure AI solutions meet standards for security, governance, model risk management, responsible AI, compliance, operational resilience, and auditability • Define, measure, and communicate product business value by connecting model performance to 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 • Deep understanding of machine learning, generative AI, large language models, retrieval systems, model evaluation techniques, data engineering, MLOps, and software development practices • Ability to evaluate technical designs and challenge architecture decisions while partnering effectively with engineering and research teams • Strong technical proficiency in Python and SQL • Knowledge of version control, CI/CD, automated testing, observability, and deployment automation • Familiarity with model risk management and AI governance in regulated industries • 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

🏖️ 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 • Online learning platform • Mentoring programs • Training and onboarding sessions • Interview accommodations, including accessible meeting rooms and captioning for virtual interviews

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