Senior Machine Learning Engineer

Work Location: Toronto, Ontario, Canada

Hours: 37.5

Line of Business: Analytics, Insights, & Artificial Intelligence

Pay Details: $115,600 - $163,200 CAD

This role is temporarily eligible for a pay premium above the posted salary range that is reassessed annually. You are encouraged to have an open dialogue with your recruiter who can provide more specific pay details for this role.

We are seeking a Senior AI/ML Engineer to drive the strategic implementation of generative AI and machine learning capabilities across TD's enterprise platforms. This individual contributor role combines deep technical expertise in large language models and cloud AI services with strategic thinking to architect and deliver production‑scale AI solutions that transform how TD serves customers globally. You will be at the forefront of TD's AI transformation, working with cutting‑edge technologies and enterprise LLM frameworks to solve complex business challenges while ensuring compliance with stringent banking regulations and responsible AI practices.

• Design and implement end‑to‑end generative AI solutions leveraging Azure AI and Google AI services to deliver transformative business changes and capabilities.
• Lead the development and optimization of production‑grade LLM applications using advanced techniques including RAG (Retrieval Augmented Generation), prompt engineering, fine‑tuning, and multi‑agent architectures to achieve measurable business outcomes
• Implement AI security frameworks such as prompt injection, adversarial attack mitigation, data poisoning detection and prompt shield
• Deliver solutions for content filtering, output monitoring and automated safety guardrails for generative AI systems.
• Architect scalable MLOps pipelines and AIOps frameworks ensuring model versioning, automated retraining, monitoring, and explainability while maintaining 99.9% availability for mission‑critical AI services
• Partner with business stakeholders to translate strategic objectives into AI/ML proof‑of‑concepts and production solutions, demonstrating clear ROI and business value through rapid prototyping and iterative development
• Drive technical strategy for expanding AI/ML capabilities across hybrid cloud landscape, evaluating emerging technologies including small language models, agentic AI, and edge deployment strategies
• Mentor platform engineers and data scientists on advanced ML techniques, LLMOps practices, and responsible AI principles through hands‑on collaboration and technical leadership
• Conduct technical due diligence on AI vendors and tools, providing recommendations for strategic investments in technologies like Cohere, Anthropic, and open‑source LLMs

• Bachelor's degree in Computer Science, Machine Learning, Mathematics, or related technical field
• Minimum 5+ years hands‑on AI/ML engineering experience with 3+ years focused on generative AI and LLM applications
• 5+ years of executive leadership experience in financial services with proven ability to influence C‑suite stakeholders and drive strategic technical initiatives
• Expert‑level proficiency in Python, including ML frameworks (PyTorch/Tensor Flow), LLM orchestration (Lang Chain/Llama Index).
• Deep hands‑on experience with Azure OpenAI Service, Azure ML Studio, Databricks MLflow, and Google Vertex AI for enterprise‑scale model deployment and management
• Strong understanding of MLOps/LLMOps practices including CI/CD for ML (Azure Dev Ops, Git Hub Actions), infrastructure‑as‑code (Terraform), and containerization (Docker/Kubernetes)
• Experience with real‑time ML inference, streaming architectures (Kafka/Pub/Sub), and edge deployment for latency‑sensitive applications
• Hands‑on experience with multi‑modal models, computer vision, and advanced NLP beyond standard LLM applications

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