Senior machine learning scientist leading predictive AI teams at TD, a major Canadian bank. Developing regression, classification, and anomaly detection models for personal banking.
About the role
- Principal Software Engineer leading MLOps team within Analytics Platform at Sun Life. Emphasizing AWS cloud services and machine learning operations responsibilities.
Responsibilities
- Provide Principal-level technical leadership for the MLOps squad within the Analytics Platform, influencing architecture and standards across multiple teams
- Design, build, and evolve production-grade MLOps and ML platform capabilities, including model lifecycle management, CI/CD, evaluation, monitoring, and governance
- Spend ~ 60% hands-on in software engineering, building high-quality, testable, maintainable services, frameworks, APIs, and shared libraries that enable ML and GenAI at scale
- Spend ~ 40% on platform, cloud, and MLOps enablement, ensuring solutions are secure, scalable, observable, and cost-effective
- Act as a technical authority for AWS-based ML platforms, leading design decisions and guiding adoption of new cloud and GenAI services
- Establish and evolve engineering and MLOps standards, patterns, and best practices across squads
- Partner closely with Architecture, Security, Risk, and Product teams to reduce delivery, operational, and model governance risk
- Lead by example through code reviews, design reviews, incident analysis, and operational improvements
- Mentor senior and intermediate engineers, raising the overall technical bar without direct people management.
Requirements
- A deep software engineering background, with a strong track record of building and operating large-scale, production systems
- Extensive hands-on experience with AWS in production, including infrastructure design, deployment, and optimization
- Strong experience with Distributed systems and cloud-native architectures
- CI/CD pipelines and automation
- Observability, reliability, and incident response
- Practical experience with MLOps, ModelOps, ML platforms, or LLMOps in enterprise environments
- Proficiency in one or more of: Python, Java, Scala, and Infrastructure-as-Code tooling (Terraform / CloudFormation)
- Ability to operate at Principal scope, influencing architecture and decisions across multiple teams and domains
- Exceptional communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
Benefits
- Wellness programs that support the three pillars of your health – mental, physical, and financial
- Professional development opportunities
- Ability to move along a variety of career paths
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Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.