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# Senior Machine Learning Engineer

- **Company:** Manulife
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $107,450.0 - $199,550.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, JIRA, Microsoft Azure, Cloud Computing, Computer Programming, Continuous Integration, Data Cleansing, Distributed Systems, Fraud Prevention and Detection, Apache Hadoop, Python (Programming Language), Machine Learning, Language Modeling, Named Entity Recognition, SQL Databases, Unstructured Data, Feature Engineering, Large Language Models, Apache Spark, Deep Learning, Generative AI, Kubernetes, Information Technology, Machine Learning Operations, Docker
- **Published:** September 20, 2026
- **Apply:** https://dejobs.org/x/x/40AEF9404DA742F09CC04D4AE2AC12CC/job/

## About the Role

* 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

Nice to Have

 * 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

## Description

* 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


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