Associate Machine Learning Engineer

Machine Learning Engineer

John Hancock's AI team works across the US Insurance business to optimize our sales and marketing activities, make life insurance easy to buy, and streamline in-force and claims operations! We have close relationships with functional leadership across the business and a strong working relationship with technology partners. As part of a 160+ member community of data scientists, John Hancock, and our parent Manulife, you will have an opportunity to network with experts across the globe.

John Hancock is a unit of Manulife Financial Corporation, a leading international financial services group offering insurance and wealth management solutions in the US, Canada, Europe, and Asia!

We are on a transformational journey. We want to remove complexity from the financial services industry, to make people's lives better and decisions easier. Being part of this transformation is hugely exciting and offers talented, ambitious people an amazing opportunity to build a career.

We are seeking a skilled Machine Learning Engineer with a strong focus on building data pipelines, AI solution development, deployment, and monitoring. The ideal candidate will have experience in data ingestion & curation, developing scalable and robust AI solutions, and deploying AI solutions in production following MLOps best practices on Microsoft Azure and Databricks platforms. A strong background in Computer vision, NLP and LLM models will be advantageous in this role.

Position Responsibilities:

• Building of GenAI and AI solutions, including but not limited to analytical model development and implementation, prompt engineering, general all-purpose programming (e.g., Python), testing, communication of results, front end and back-end integration, and iterative development with business subject matter expertise.
• Designing and solutioning AI/GenAI architectures for business teams, specifically for plugin-based solutions and custom AI/GenAI application builds.
• Partner with data engineers and architects to design and implement scalable database solutions and data models, organizing both structured and unstructured data.
• Develop processes for data cleansing, enrichment, and validation to improve quality and reliability.
• Collaborate with data scientists to develop and deploy machine learning models in cloud following best practices.
• Monitor, solve, and optimize data pipelines for performance and efficiency.
• Partner with IT and technology teams to put together data architecture designs, integration procedures, and data management workflows.
• Partner with data and platform partners to implement the best practices in managing data and platforms, supporting AI development and deployment at scale.
• Develop automation scripts and tools to ease the deployment, scaling, and management of data systems within the cloud environment.
• Continuously monitor and improve the performance of AI solutions through data analysis and testing.
• Strong communication to help business partners better understand the use of data, ML models, and AI solutions.

Required Qualifications:

• Experienced in developing and deploying models using AI and GenAI technologies in cloud.
• Experienced in data modeling, ETL/ELT development, and data warehousing.
• Master/PhD degree in a quantitative field such as Data Science, Engineering, Computer Science or related technical field.

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.