1 day ago
Toronto, CanadaSenior
Responsibilities
- Design and implement end-to-end generative AI solutions leveraging Azure AI and Google AI services.
- Develop and optimize production-grade LLM applications using RAG, prompt engineering, fine-tuning, and multi-agent architectures.
- Implement AI security frameworks, including prompt-injection protection, adversarial-attack mitigation, data-poisoning detection, and prompt shields.
- Deliver content filtering, output monitoring, and automated safety guardrails for generative AI systems.
- Architect scalable MLOps and AIOps pipelines with model versioning, automated retraining, monitoring, explainability, and 99.9% availability.
- Translate business objectives into AI/ML proofs of concept and production solutions and demonstrate ROI through rapid prototyping.
- Drive technical strategy across a hybrid-cloud environment and evaluate small language models, agentic AI, and edge-deployment strategies.
- Mentor platform engineers and data scientists on advanced ML, LLMOps, and responsible AI practices.
- Conduct technical due diligence on AI vendors and tools, including Cohere, Anthropic, and open-source LLMs.
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Mathematics, or a related technical field.
- At least 5 years of hands-on AI/ML engineering experience, including at least 3 years focused on generative AI and LLM applications.
- At least 5 years of executive leadership experience in financial services with the ability to influence C-suite stakeholders and drive strategic technical initiatives.
- Expert-level Python proficiency, including PyTorch or TensorFlow and LangChain or LlamaIndex.
- 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 and LLMOps, including Azure DevOps, GitHub Actions, Terraform, Docker, and Kubernetes.
- Experience with real-time ML inference, Kafka or Pub/Sub streaming architectures, and edge deployment for latency-sensitive applications.
- Hands-on experience with multimodal models, computer vision, and advanced NLP beyond standard LLM applications.
Benefits
- Base salary of $115,600–$163,200 CAD with a temporarily eligible pay premium reassessed annually.
- Health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs.
- Regular development and performance conversations, training programs, an online learning platform, mentoring programs, and training and onboarding sessions.
- Accessibility accommodations are available throughout the interview process.
- The role is located in Toronto, Ontario, Canada, with a 37.5-hour work week and provincial employment regulations applying.
Tech Stack
Categories
About TD bank
TD Bank Group provides retail and commercial banking, credit cards, mortgages, wealth management, insurance, and capital-markets services to consumers, businesses, and institutional clients. Headquartered in Toronto and founded in 1955, it operates across Canada and the eastern United States. The company generates revenue from interest income, fees, and trading activities and is publicly traded on the TSX and NYSE under the symbol TD.