MLOps Engineer

Manulife Insurance Malaysia; Toronto; Hybrid; CAD 75,000 - 141,000; Full time

Job summary

A leading company in financial services is seeking a motivated Machine Learning Engineer focused on MLOps architecture and tooling. This role includes responsibilities in maintaining Python libraries, enhancing CI/CD pipelines, and collaborating with project teams to drive innovation in AI and MLOps. The ideal candidate will have a strong background in cloud solutions and a passion for developing advanced AI solutions.

Benefits

Health and dental benefits

Flexible working environment

Retirement savings plans

Paid time off program including holidays and vacation

Employee assistance programs

Qualifications

• 3-4 years of experience in building and maintaining MLOps infrastructure and tooling.
• Proficiency in Python for developing libraries and applications.
• Exposure to experiment tracking tools and monitoring solutions.

Responsibilities

• Assist in implementing and managing CI/CD pipelines.
• Work with AI/ML project teams to adopt MLOps tools.
• Capture feedback to improve MLOps tools and features.

Skills

Python

MLOps

CI/CD

Communication

Cloud computing

Education

Bachelor's or Master's in Computer Science, Data Science, or related field

Tools

Jenkins

Azure

Databricks

Docker

Kubernetes

MLFlow

Job description

time left to apply End Date: June 14, 2025 (15 days left to apply)

job requisition id JR25011433

Manulife is seeking a motivated and dedicated Machine Learning Engineer with a focus on MLOps architecture, tooling, and standards development. In this key role, you will be responsible for maintaining and enhancing Python libraries, lightweight applications, and CI/CD pipelines that enable our AI/ML developers to efficiently track experiments, conduct testing, streamline deployment, and monitor model health. By using AI to more efficiently deliver AI, you will collaborate with AI/ML project teams to facilitate the adoption of MLOps tools and standards, incorporating feedback to continuously refine our tooling features.

You will join our Global Advanced Analytics team and be a driving force in shaping the future of AI/MLOps with a focus on using AI to more efficiently deliver AI. We are dedicated to building brand-new MLOps architecture, tooling, and standards to empower our AI/ML developers.

You will also contribute to the development of tools and standards to operationalize LLM and Generative AI use-cases, ensuring seamless integration with existing MLOps practices and infrastructure. We aim to enhance operational efficiency and innovation. If you are passionate about the evolving landscape of LLM and Generative AI, we want to hear from you!

Position Responsibilities

• CI/CD Pipeline Management: Assist in implementing and managing CI/CD pipelines to automate testing and deployment processes, ensuring efficient and reliable operations.
• Collaboration and Support: Work with AI/ML project teams across segments to help them adopt MLOps tools and standards, providing guidance and support as needed.
• Stakeholder Engagement: Capture feedback from team members to improve and enhance MLOps tools and features, ensuring they meet the evolving needs of our teams.
• Standards Development: Contribute to defining and implementing effective practices and standards for MLOps processes to ensure efficient and streamlined operations.
• Industry Insights: Stay updated with industry advancements in LLM and Generative AI models, enhancing MLOps capabilities to support LLM Ops needs.
• Cross-Functional Collaboration: Work multi-functionally with data scientists, software engineers, architects, and operations teams to ensure flawless integration and operation of MLOps and LLM Ops solutions

Required Qualifications:

• Educational Background: Bachelor's, Master's, or equivalent experience in Computer Science, Data Science, Statistics, or a related field.
• MLOps Experience: 3-4 years of experience in building and maintaining MLOps infrastructure and tooling.
• Software Development: Proficiency in Python and experience with developing libraries and applications.
• CI/CD Tools: Experience with CI/CD tools and pipelines, preferably Jenkins.
• Cloud and Containerization: Familiarity with cloud platforms (preferably Azure), ML development environments (Databricks), and containerization technologies (Docker, Kubernetes).
• Experiment Tracking and Monitoring: Exposure to experiment tracking tools (e.g., MLFlow) and monitoring solutions.
• Strong communication skills, able to explain complex concepts to various collaborators.
• Understanding of ML Lifecycle: Basic understanding of the machine learning lifecycle and standard methodologies in MLOps.
• LLM/GenAI Models: Basic understanding of LLM/GenAI models and their operational requirements.

Preferred Qualifications:

• Databricks Ecosystem Expertise: Hands-on expertise in the Databricks ecosystem, particularly model management using Unity Catalog.
• Full Stack Engineering Exposure: Ability to build proof of concepts/demos including both front-end and back-end development.
• Adaptability: Demonstrated proficiency in quickly picking up new frameworks and libraries.

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.

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 [e-mail] .

Referenced Salary Location

Toronto, Ontario

Working Arrangement

Manulife is seeking a motivated and dedicated Machine Learning Engineer with a focus on MLOps architecture, tooling, and standards development. In this key role, you will be responsible for maintaining and enhancing Python libraries, lightweight applications, and CI/CD pipelines that enable our AI/ML developers to efficiently track experiments, conduct testing, streamline deployment, and monitor model health. By using AI to more efficiently deliver AI, you will collaborate with AI/ML project teams to facilitate the adoption of MLOps tools and standards, incorporating feedback to continuously refine our tooling features.

You will join our Global Advanced Analytics team and be a driving force in shaping the future of AI/MLOps with a focus on using AI to more efficiently deliver AI. We are dedicated to building brand-new MLOps architecture, tooling, and standards to empower our AI/ML developers.

You will also contribute to the development of tools and standards to operationalize LLM and Generative AI use-cases, ensuring seamless integration with existing MLOps practices and infrastructure. We aim to enhance operational efficiency and innovation. If you are passionate about the evolving landscape of LLM and Generative AI, we want to hear from you!

Position Responsibilities

• CI/CD Pipeline Management: Assist in implementing and managing CI/CD pipelines to automate testing and deployment processes, ensuring efficient and reliable operations.
• Collaboration and Support: Work with AI/ML project teams across segments to help them adopt MLOps tools and standards, providing guidance and support as needed.
• Stakeholder Engagement: Capture feedback from team members to improve and enhance MLOps tools and features, ensuring they meet the evolving needs of our teams.
• Standards Development: Contribute to defining and implementing effective practices and standards for MLOps processes to ensure efficient and streamlined operations.
• Industry Insights: Stay updated with industry advancements in LLM and Generative AI models, enhancing MLOps capabilities to support LLM Ops needs.
• Cross-Functional Collaboration: Work multi-functionally with data scientists, software engineers, architects, and operations teams to ensure flawless integration and operation of MLOps and LLM Ops solutions

Required Qualifications:

• Educational Background: Bachelor's, Master's, or equivalent experience in Computer Science, Data Science, Statistics, or a related field.
• MLOps Experience: 3-4 years of experience in building and maintaining MLOps infrastructure and tooling.
• Software Development: Proficiency in Python and experience with developing libraries and applications.
• CI/CD Tools: Experience with CI/CD tools and pipelines, preferably Jenkins.
• Cloud and Containerization: Familiarity with cloud platforms (preferably Azure), ML development environments (Databricks), and containerization technologies (Docker, Kubernetes).
• Experiment Tracking and Monitoring: Exposure to experiment tracking tools (e.g., MLFlow) and monitoring solutions.
• Strong communication skills, able to explain complex concepts to various collaborators.
• Understanding of ML Lifecycle: Basic understanding of the machine learning lifecycle and standard methodologies in MLOps.
• LLM/GenAI Models: Basic understanding of LLM/GenAI models and their operational requirements.

Preferred Qualifications:

• Databricks Ecosystem Expertise: Hands-on expertise in the Databricks ecosystem, particularly model management using Unity Catalog.
• Full Stack Engineering Exposure: Ability to build proof of concepts/demos including both front-end and back-end development.
• Adaptability: Demonstrated proficiency in quickly picking up new frameworks and libraries.

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.

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 [e-mail] .

Referenced Salary Location

Toronto, Ontario

Working Arrangement

Hybrid

Salary range is expected to be between

$75,880.00 CAD - $140,920.00 CAD

If you are applying for this role outside of the primary location, please contact [e-mail] 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 [e-mail] for more information about U.S.-specific paid time off provisions.