Employer: John Hancock Life Insurance Company (USA)
Job Site: 200 Berkeley Street, Boston, MA 02116
Job Title: Senior Machine Learning Engineer
Job Duties:
Package models, automate workflows, and operationalize analytics solutions to generate business value for organization’s insurance division as member of U.S. based Advanced Analytics Team. Duties include:
- Design, recommend, and implement platforms and infrastructure using MLOps/LLMOps best practices;
- Collaborate with data scientists and data engineers to design and implement scalable and efficient machine learning pipelines;
- Evaluate and optimize machine learning models for performance and scalability;
- Deploy machine learning models into production and monitor performance;
- Manage data science infrastructure to streamline model development and deployment;
- Support development and deployment of high-quality Generative AI technologies including prompt engineering and RAG applications, and fine-tuning LLM models using Azure AI Studio;
- Propose appropriate tools including languages, libraries, and frameworks for implementing projects;
- Work closely with infrastructure architects to design scalable and efficient solutions;
- Collaborate with cross-functional teams to integrate machine learning models into existing systems and processes;
- Keep abreast of latest advancements in machine learning, MLOps, and LLMOps techniques, and contribute to continuously improving organization’s machine learning capabilities; and
- Mentor associates and peers on MLOps best practices.
Work Arrangement requirement: Hybrid from Boston office (3 days from office, 2 days from home)
Minimum Requirements:
Master’s degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.
Experience must include the following, which may be gained concurrently:
Minimum Requirements:
Master’s degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.
Experience must include the following, which may be gained concurrently:
Minimum Requirements:
Master’s degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.
Experience must include the following, which may be gained concurrently:
- 3 years of experience developing and deploying machine learning models for model training, optimization, evaluation, and production deployment through APIs, microservices, or cloud-based serving infrastructure using Python, TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost.
- 3 years of experience deploying and managing infrastructure using Linux OS, containerization technologies (Docker, Kubernetes), relational databases (PostgreSQL, MySQL, and Oracle) and NoSQL databases (MongoDB, Cassandra, Elasticsearch and Redis) using AWS, Azure or GCP cloud platforms.
- 3 years of experience designing and building scalable ETL pipelines and feature engineering workflows for large-scale datasets using distributed processing frameworks including Apache Spark (PySpark, Spark SQL), Hadoop ecosystem tools, or cloud-based big data services including Databricks and EMR.
- 2 years of experience developing and deploying Large Language Models including BERT, GPT-series, T5, or LLaMA, or other transformer-based NLP models using cloud-based platforms and open-source frameworks.
- 3 years of experience designing hybrid machine learning systems combining rule-based decision engines with ML models for fraud detection, compliance, claims adjudication, or automated decision-making in regulated environments.
- 3 years of experience applying machine learning algorithms, statistical modeling, and data analysis techniques for model optimization, generating actionable insights, and working with structured and unstructured data to solve business problems in financial services, fintech, insurance, or other regulated industries.
- 3 years of experience with Agile development methodologies including Scrum, Kanban, or SAFe for sprint planning, iterative development cycles, and cross-functional team collaboration in enterprise environments.
- 2 years of experience developing and deploying computer vision models for document processing, OCR, information extraction, or image classification using OpenCV, Tesseract, or cloud-based vision APIs.
Salary: $175,000 per year
The role being advertised is an existing vacancy.
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 [email protected].
Referenced Salary Location
Boston, MassachusettsWorking Arrangement
Salary range is expected to be between
$107,450.00 USD - $199,550.00 USDEmployees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. 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. If you are applying for this role outside of the primary location, please contact [email protected] for the salary range for your location.
Manulife/John Hancock 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/401(k) savings plans and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in the U.S. includes up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year, and we offer the full range of statutory leaves of absence.
We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.
Know Your Rights I Family & Medical Leave I Employee Polygraph Protection I Right to Work I E-Verify
Company: John Hancock Life Insurance Company (U.S.A.)Skills Required
- Master's degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or a related field
- 3 years of machine learning experience
- 3 years developing and deploying machine learning models using Python, TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost
- 3 years deploying and managing infrastructure using Linux, Docker, Kubernetes, relational and NoSQL databases, and AWS, Azure, or GCP
- 3 years designing scalable ETL pipelines and feature engineering workflows using Apache Spark, Hadoop, Databricks, EMR, or related big data services
- 2 years developing and deploying transformer-based large language models, including BERT, GPT-series, T5, or LLaMA
- 3 years designing and building hybrid machine learning and rule-based systems for fraud detection, compliance, claims adjudication, or automated decision-making in regulated environments
- 3 years applying machine learning, statistical modeling, and data analysis techniques in financial services, fintech, insurance, or other regulated industries
- 3 years using Agile development methodologies, including Scrum, Kanban, or SAFe, in enterprise environments
- 2 years developing and deploying computer vision models for document processing, OCR, information extraction, or image classification using OpenCV, Tesseract, or cloud vision APIs
Manulife Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Manulife and has not been reviewed or approved by Manulife.
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Healthcare Strength — Healthcare coverage is portrayed as comprehensive, spanning medical, dental, prescription drugs, vision, critical illness, and short- and long-term disability. Mental-health support is emphasized via EAP-style services and high annual coverage limits in some regions, alongside wellness programs and navigation tools.
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Retirement Support — Retirement offerings are positioned as a meaningful part of total rewards, including group RRSP/defined contribution pension options and employer matching in some cases. Ownership-related programs such as share purchase/stock options are also described as available for eligible employees.
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Flexible Benefits — Benefits are described as robust and flexible, with customizable packages and spending-account style options in some plans. Digital tools (mobile app/claims) and reward-linked wellness programs are framed as making benefits easier to use and more engaging.
Manulife Insights
What We Do
Manulife is a leading international financial services group that helps people make their decisions easier and lives better. With our global headquarters in Toronto, we operate as Manulife across our offices in Canada, Asia, and Europe, and primarily as John Hancock in the United States. We have more than 40,000 employees, over 116,000 agents serving ~34 million customers worldwide, and over $1.3 trillion in assets under management and administration. Visit www.Manulife.com to find out more. For Manulife terms of use, please visit http://bit.ly/SM_Terms






