Machine Learning Engineer

We are looking for a driven and innovative Machine Learning Engineer to join our Global Retirement & Wealth AI team! Within our AI and Generative AI initiatives, you will compose, build, and scale production-grade GenAI solutions. These solutions improve participant outcomes, advisor productivity, and operational efficiency across our Retirement and Wealth businesses. Your work will power experiences such as participant and advisor copilots, RAG over plan and product documents, personalization and retirement readiness guidance, workflow automation and intelligent compliance enablement!

Position Responsibilities:

• Build GenAI Products End-to-End: Design, implement, and productionize LLM-powered applications (APIs, microservices, and UI-backed services) including RAG pipelines, tool/Function-calling, agentic workflows, and prompt orchestration for participant, plan sponsor, advisor, and operations use cases.
• Data & Retrieval Engineering: Partner with data engineers and SMEs to source, model, and optimize structured and unstructured data (plan documents, product guides, call notes, knowledge bases). Implement embedding pipelines, chunking strategies, retrieval optimization, and vector search (e.g., Azure AI Search, Redis/MongoDB/LanceDB).
• Modeling & Optimization: Apply classical ML and GenAI techniques (prompt engineering, fine-tuning, RAG, reranking, guardrails) to improve accuracy, latency, cost, and hallucination control.
• MLOps & LLMOps: Ship reliable services with CI/CD, infrastructure-as-code, model/prompt versioning, MLflow/experiment tracking, observability, canary releases, and automated evaluation suites (offline & online A/B).
• Security, Privacy, and Compliance: Implement and document controls for PII/financial data, RBAC, prompt injection defenses, content filtering, red-teaming, and model risk governance aligned to regulatory expectations (e.g., auditability, explainability, record-keeping).
• Partner Collaboration: Translate business goals into technical plans with Product, Operations, Contact Center, Distribution, Compliance, Risk, and Legal. Convert requirements into robust builds and SLAs; standardize methods into engineering guidelines reusable across teams.
• Continuous Innovation: Know the latest on LLM and retrieval research, model choices, evaluation techniques, and platform capabilities and pragmatically apply them to Retirement & Wealth use cases at scale.

Required Qualifications:

• Education: Bachelor’s or Master’s in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.
• Experience: 4+ years building ML/AI solutions, including 2+ years hands-on with Generative AI (RAG, prompt engineering, function/tool calling, agentic patterns). Consistent track record of shipping production systems with measurable business value.
• Programming & Frameworks: Strong Python and SQL; experience with LangChain, LangGraph, Semantic Kernel, CrewAI, or ADK; familiarity with Hugging Face, PyTorch, and modern embedding/reranker stacks.
• Cloud & Data: Practical experience on Azure (preferred) and Databricks/Spark, Delta Lake/Unity Catalog, feature stores, API development, containerization (Docker, Kubernetes), and event/messaging (e.g., Kafka/Event Hubs).
• RAG & Retrieval: Hands-on with embedding models, chunking, metadata enrichment, vector databases/search, hybrid search and retrieval evaluation/telemetry.
• MLOps/LLMOps: CI/CD (e.g., GitHub Actions/Azure DevOps), model and timely lifecycle management, experiment tracking (MLflow), observability, evaluation harnesses, and optimization of expenses and response times.
• Communication: Excellent ability to translate complex ML/LLM concepts into business outcomes for both technical and non-technical partners; clear documentation and design articulation.

Preferred Qualifications:

• Safety & Governance: Exposure to model risk management, prompt and content safety guardrails, adversarial testing/red-teaming, and responsible AI practices.
• Fine-Tuning: Practical experience with LoRA/PEFT, supervised fine-tuning, or instruction-tuning pipelines; evaluation with task-specific metrics and human-in-the-loop review.
• Platform & Tooling: Familiarity with Azure OpenAI, Databricks (including Unity Catalog), API design, microservices, and serverless patterns.
• Experimentation: Experience running online experiments (A/B, interleaving), prompt/model eval frameworks, quality dashboards, and cost/latency SLOs.
• Full-Stack Awareness: Comfortable building POCs/demos across backend services and lightweight frontends to accelerate partner feedback.

When you join our team:

• We’ll empower you to learn and grow the career you want.
• We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team, we’ll support you in shaping the future you want to see.

#LI-Hybrid

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact recruitment@manulife.com.

Referenced Salary Location

Salary range is expected to be between

If you are applying for this role outside of the primary location, please contact recruitment@manulife.com for the salary range for your location. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance.

Manulife offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact recruitment@manulife.com for more information about U.S.-specific paid time off provisions.