Senior Machine Learning Engineer
External
Manulife · Boston, MAPrepare for this interview
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About the role
Join John Hancock's AI team and help transform the insurance experience through advanced analytics and intelligent automation. You'll work at the intersection of business and technology to build scalable AI solutions that enhance customer experience, simplify processes, and drive smarter decisions. As part of a global community of 260+ data scientists and AI professionals across Manulife, you'll collaborate with experts worldwide on high-impact initiatives. We are on a transformation journey to remove complexity from financial services and make decisions easier for our customers.
Responsibilities
- Design, build, and operationalize machine learning models-from experimentation to scalable production systems (including classical ML, deep learning, and LLM-based solutions)
- Develop and maintain end-to-end ML pipelines with CI/CD, monitoring, and model performance tracking
- Lead technical design reviews and define architecture standards for scalability, reliability, and security
- Partner with data scientists, engineers, and business stakeholders to deliver AI solutions aligned to business goals
- Apply and champion MLOps best practices across the full model lifecycle
- Mentor junior engineers and contribute to a strong engineering culture
- What You Bring
- Master's or PhD in Computer Science, Engineering, or a related quantitative field
- 5+ years of experience delivering machine learning solutions in production
- Strong programming skills in Python (Java/SQL a plus)
- Hands-on experience with NLP and document understanding (e.g., classification, entity extraction, relationship extraction)
- Experience working with unstructured data (PDFs, images) using vision/language models and OCR
- Strong understanding of the AI lifecycle: data preparation, feature engineering, model development, deployment, and monitoring
- Experience with distributed computing (e.g., Spark, Hadoop) and cloud platforms (AWS, GCP, or Azure)
- Familiarity with Docker, Kubernetes, CI/CD pipelines, and production-grade engineering practices
Requirements
- Experience with fraud detection, anomaly detection, or deepfake detection
- Exposure to generative AI, LLM fine-tuning, or agent-based systems
- Experience working in agile environments (e.g., JIRA)
- What Drives Success
- Customer-first mindset with a focus on impact
- Curiosity and passion for applying emerging AI technologies
- Ownership and accountability in fast-paced environments
- Strong collaboration across cross-functional teams
- Commitment to integrity and inclusion
Benefits
Additional Information
Senior Machine Learning Engineer
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