Associate machine learning engineer

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 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.