Machine Learning Engineer

Munich Re; Toronto; Hybrid; CAD 80,000 - 120,000; Full time

Job summary

An established industry player seeks a dynamic Machine Learning Engineer to enhance customer experience through innovative data solutions. In this role, you will leverage cutting-edge models and collaborate with talented teams to operationalize AI systems. You will manage the model lifecycle and contribute to groundbreaking advancements in medical risk assessment. This forward-thinking company offers a hybrid work environment, generous benefits, and a commitment to professional development. Join a team that values diversity, inclusion, and transformative change in the life insurance sector.

Benefits

Flexible health and dental benefits

Company-paid Health Spending Account

DC Pension Plan with employer contribution

Generous vacation and personal days

Unlimited access to LinkedIn Learning

Maternity and Parental Leave top-up

Employee Referral Program

Recognition & Rewards Platform

Qualifications

• 2-3 years of experience in deploying models and managing the model lifecycle.
• Intermediate knowledge of software development principles.

Responsibilities

• Collaborate on developing machine learning / AI systems from prototyping to production.
• Design, test, build, and maintain backend infrastructure for model lifecycle.

Skills

Machine Learning

Data Science

Software Development

Technical Communication

Cloud Computing

Data Manipulation

Education

Bachelor’s Degree in Engineering

Bachelor’s Degree in Mathematics

Bachelor’s Degree in Computer Science

Bachelor’s Degree in Data Science

Bachelor’s Degree in Physics

Tools

MLFlow

Flyte

Sagemaker

Docker

Kubernetes

Terraform

scikit-learn

PyTorch

Job description

Position Overview

Munich Re sees the use of medical data as instrumental in enhancing the customer experience and expanding insurability for life insurance. Integrated Analytics (IA) leads this effort in the US and Canada. Individuals in the role of Machine Learning Engineer will use their knowledge of software engineering and data science to operationalize solutions that leverage proprietary and off-the-shelf models to solve key challenges in medical risk assessment.

• In the past year we have:
• Automated risk assessment for medical impairments using Electronic Health Records
• Deployed 10+ models to production in partnership with data science
• Expanded MLOps infrastructure to support data science workflows and operationalize Munich Re’s AI Governance program

Your Role:

• Collaborate closely with team members on developing machine learning / AI systems from prototyping to production.
• Leverage proprietary and off-the-shelf (e.g., Llama, GPT-4o, NuExtract) models to enable new risk assessment paradigms.
• Design, test, build, and maintain the backend infrastructure to manage the model lifecycle.
• Work with existing data science and engineering groups at Munich Re to develop model management best practices.

Your Profile:

• Bachelor’s Degree in Engineering, Mathematics, Computer Science, Data Science, Physics
• 2-3 years of experience in deploying models and managing the model lifecycle
• Experience working with data and models through the model lifecycle with emphasis on CI/CD for ML, versioning, reproducibility
• Intermediate knowledge of principles of software development
• Strong written technical communication skills
• Ability to manipulate large structured and unstructured datasets
• Familiarity with cloud computing

Nice to have:

• Infrastructure: experience with ML platform / orchestration tools (e.g., MLFlow, Flyte, Sagemaker, etc); familiarity with containerization (e.g., Docker), orchestration (e.g., Kubernetes) and infrastructure-as-code (e.g., Terraform)
• Machine Learning: experience with Hugging Face, modelling libraries (e.g., scikit-learn, PyTorch), 3rd party LLMs (OpenAI models, Claude, etc.)

Together, we engage with everything we have and are, to help humankind act braver and better.

As the world’s leading reinsurance company with more than 40,000 employees in over 50 locations around the globe, Munich Re introduces a paradigm shift in the way you think about insurance. By turning uncertainty into manageable risk, we enable fundamental change. We recognize Diversity, Inclusion, and Belonging as a key priority with a culture that welcomes different thoughts and opinions. We dare to think big and are continuously innovating on behalf of our clients.

Our data, our technology, and our teams place us in a unique position to drive transformative change in the life insurance industry. We invest strategically in our world class talent, offering our employees a work experience that promotes professional development, innovation, and rewards high performance.

What Can We Offer You?

We are pleased to offer our employees great benefits and resources to support their mental, physical and financial wellbeing. These include:

• An engaging and collaborative environment that promotes continuous learning and development
• A hybrid work environment that combines weekly in-office and remote days with Meeting-Free lunch hours and Focus Friday afternoons
• A great compensation package including annual company bonus
• Market leading company-paid flexible health and dental benefits, starting on your first day
• Flexible dollars provided by the company to put towards Health Spending Account and/or Wellness Spending Account
• Immediate participation in DC Pension Plan with an automatic 5% employer contribution, plus optional company match
• Generous time off including vacation, personal days, unplanned time, Statutory Holidays and company-wide early closure half-days
• Learning and development programs and resources, including unlimited access to LinkedIn Learning, Education Assistance Program and reimbursement for professional fees
• Maternity, Parental & Adoption Leave top-up program
• Employee Referral Program, Recognition & Rewards Platform

Please note that only candidates who are selected for interview will be contacted directly. We thank all candidates for their interest.

Munich Re is committed to providing a work environment that is inclusive and free of employment barriers and discrimination. Accommodations will be made for qualified applicants with a disability throughout the recruitment process. If you receive a request for an interview and you have a disability which will require an accommodation to support your participation, please contact [e-mail] as soon as practical so that suitable accommodations can be arranged.