Senior ML Engineer — Hybrid, Lead ML Platform & LLMOps

manulife; Boston (MA); Hybrid; USD 158,000 - 193,000; Full time

Job summary

Manulife seeks a Senior Machine Learning Engineer to design and implement production-grade ML platforms using MLOps/LLMOps best practices. You will work with data scientists and engineers to build scalable pipelines, evaluate models, and deploy them with robust monitoring.

The role also emphasizes mentoring peers in MLOps and staying current with Generative AI advances. You will collaborate across teams, craft scalable solutions with Docker/Kubernetes on cloud platforms, and contribute to

Qualifications

• Master's degree in Data Science, CS, CE, or related field with 3+ years ML experience.
• 3+ years deploying ML models via APIs, microservices, or cloud-based serving infra.
• 3+ years using Linux, Docker/Kubernetes, and cloud platforms (AWS/Azure/GCP).
• 3+ years building ETL pipelines and feature engineering for large data.
• 2+ years developing and deploying LLMs and transformer models.

Responsibilities

• Design, recommend, and implement platforms and infrastructure using MLOps/LLMOps best practices.
• Collaborate with data scientists and engineers to design scalable ML pipelines.
• Evaluate and optimize models for performance and scalability.
• Deploy models into production and monitor performance.
• Mentor associates on MLOps best practices.

Education

Master's degree in Data Science, Computer Science, Computer Engineering, or related field

Tools

Python

TensorFlow

PyTorch

Scikit-learn

Keras

XGBoost

OpenCV

Tesseract

Docker

Kubernetes

Linux

PostgreSQL

MySQL

Oracle

MongoDB

Cassandra

Elasticsearch

Redis

Apache Spark

PySpark

Spark SQL

Databricks

EMR

Azure AI Studio

Job description

Manulife seeks a Senior Machine Learning Engineer to design and implement production-grade ML platforms using MLOps/LLMOps best practices. You will work with data scientists and engineers to build scalable pipelines, evaluate models, and deploy them with robust monitoring.

The role also emphasizes mentoring peers in MLOps and staying current with Generative AI advances. You will collaborate across teams, craft scalable solutions with Docker/Kubernetes on cloud platforms, and contribute to