MLOps Engineer

Job Title: Machine Learning/MLOps Engineer

Location: SFO, CA, Columbus, OH, Jersey City, NJ (Hybrid – 3 days from office)

Duration: 12 Months

Role Overview

We are looking for a hands-on ML Ops Engineer with strong experience in machine learning model development, deployment, and productionization. The ideal candidate should have practical experience with churn prediction/modeling, XGBoost, Python, AWS SageMaker, and MLOps tools such as MLflow or Weights & Biases.

Key Responsibilities & Skills:

· Strong Python programming with hands-on experience in XGBoost, predictive analytics, and churn modeling.

· Expertise in AWS SageMaker for model training, deployment, optimization, and monitoring.

· Experience with MLflow and Weights & Biases (W&B) for experiment tracking, model registry, and versioning.

· Experience with HPE Swarm Learning for decentralized, privacy-preserving, distributed model training.

· Knowledge of model explainability and feature importance.

· Build automated ML pipelines, CI/CD workflows, model monitoring, drift detection, and retraining processes.

· Experience with Docker, AWS S3, Git, and integrating ML models into enterprise applications.

· Collaborate with data scientists and engineering teams to support the Algorithm Workbench, reproducibility, data integrity, and GxP compliance.

Skills: XGBoost/churn modeling, Python, AWS Sagemaker, and MLflow/weights & Biases for the MLOps.