Associate Machine Learning Engineer

Manulife Financial; Toronto; Hybrid; CAD 60,000 - 114,000; Full time

Job summary

An established industry player is seeking a Machine Learning Engineer to join their Group Advanced Analytics team. This role involves packaging models, automating workflows, and operationalizing analytics solutions to drive business value. The ideal candidate will have a strong programming background in Python and experience with machine learning libraries, DevOps practices, and cloud-native architecture. You will collaborate with data scientists and engineers to create impactful machine learning solutions while mentoring peers in best practices. Join a forward-thinking company that values innovation, diversity, and professional growth, offering a competitive salary and comprehensive benefits.

Benefits

Health Insurance

Dental Insurance

Mental Health Support

Flexible Work Policies

Professional Development Opportunities

Retirement Savings Plans

Paid Time Off

Employee Assistance Programs

Qualifications

• Hands-on experience with large-scale software engineering systems.
• Proven experience in operationalizing code through DevOps pipelines.

Responsibilities

• Design and implement scalable machine learning pipelines.
• Deploy models into production and monitor their performance.

Skills

Python

Machine Learning

Data Engineering

Software Engineering

DevOps

SQL

Large Language Models

ETL Pipelines

Cloud Computing

Agile Product Delivery

Education

Bachelor's in Computer Science or Engineering

Graduate Degree

Tools

Git

Jenkins

Docker

Kubernetes

Azure ML

Databricks

Azure Data Factory

Job description

The Opportunity

The Machine Learning Engineer will join the Group Advanced Analytics team, focusing on packaging models, automating workflows, and operationalizing analytics solutions to deliver business value across JH/Manulife. The ideal candidate should be an advanced programmer with a strong grasp of Data Science, Data Engineering, application development, software engineering, and DevOps.

Responsibilities

• Collaborate closely with Data Scientists and Data Engineers to design and implement scalable, efficient machine learning pipelines that meet business needs.
• Evaluate machine learning models to ensure optimal performance and scalability, making necessary adjustments to improve outcomes.
• Deploy machine learning models into production environments, ensuring seamless integration, and continuously monitor their performance to maintain reliability and accuracy.
• Manage and oversee data science infrastructure to streamline the model development and deployment process, ensuring efficient workflows.
• Propose and implement appropriate tools, including languages, libraries, and frameworks, to enhance project execution and outcomes.
• Work in collaboration with infrastructure architects to develop scalable and efficient solutions that align with organizational goals and technological capabilities.
• Collaborate with multi-functional teams to integrate machine learning models into existing systems and processes, ensuring a smooth transition and effective implementation.
• Stay ahead of the latest advancements in Machine Learning (ML), Artificial Intelligence (AI), and Generative AI (GenAI) to incorporate innovative techniques and technologies into projects.
• Mentor peers and provide guidance on ML/LLMOps standard practices, fostering a culture of continuous learning and improvement within the team.

How will you create impact?

Machine Learning Engineers (MLEs) are integral to the central team, playing a crucial role in amplifying the impact of the Group Advanced Analytics by supporting various Data Science teams with new development and deployments. They are responsible for providing infrastructure and deployment support, ensuring the seamless operationalization of models and MLOps processes, and establishing standardized methodologies across all teams to enhance efficiency and consistency.

What motivates you?

• You obsess about customers, listen, engage and act for their benefit.
• You think big, with curiosity to discover ways to use your agile approach and enable business outcomes.
• You thrive in teams and enjoy getting things done together.
• You take ownership and build solutions, focusing on what matters.
• You do what is right, work with integrity and speak up.
• You share your humanity, helping us build a diverse and inclusive work environment for everyone.

What we are looking for

• A bachelor's degree in computer science, engineering, or a related field is required, with a graduate degree being preferred.
• Extensive hands-on experience with large-scale software engineering systems, emphasizing the development and deployment of machine learning models.
• Proven experience in operationalizing code through DevOps pipelines, including tools like Git, Jenkins, and code scanning technologies.
• Strong programming skills in Python, with experience in machine learning libraries like TensorFlow, PyTorch, or scikit-learn.
• Strong familiarity with MLOps practices, including model monitoring, versioning, and lifecycle management to ensure robust and scalable deployment of machine learning solutions.
• Advanced knowledge of SQL and experience working with relational databases, alongside proficiency in RDBMS and NoSQL databases.
• Experience in infrastructure management, including cloud computing, Linux OS, networks, Docker, and Kubernetes.
• Expertise in cloud-native architecture, preferably using the Azure stack, with skills in Azure ML, Databricks (Spark), and Azure Data Factory as valuable assets.
• Proficient in building ETL pipelines for feature engineering on large-scale datasets using Spark.
• Experience with Large Language Models (LLMs) including proprietary or open source models.
• Ability to balance urgency with the delivery of high-quality, pragmatic solutions.
• Expertise in delivering analytics and machine learning products, with a deep understanding of agile product delivery in enterprise environments.

What can we offer you?

• A competitive salary and benefits packages.
• A growth trajectory that extends upward and outward, encouraging you to follow your passions and learn new skills.
• A focus on growing your career path with us.
• Flexible work policies and strong work-life balance.
• Professional development and leadership opportunities.

Our commitment to you

• Values-first culture: We lead with our Values every day and bring them to life together.
• Boundless opportunity: We create opportunities to learn and grow at every stage of your career.
• Continuous innovation: We invite you to help redefine the future of financial services.
• Delivering the promise of Diversity, Equity and Inclusion: We foster an inclusive workplace where everyone thrives.
• Championing Corporate Citizenship: We build a business that benefits all partners and has a positive social and environmental impact.

Primary Location: Toronto, Ontario

Working Arrangement: Hybrid

Salary range is expected to be between: $60,900.00 CAD - $113,100.00 CAD

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.