MLOps Engineer

Job Title: Machine Learning Engineer/ML Ops Engineer

Location: SFO, CA (Hybrid – 3 days from office)

Duration: 12 Months

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

We are seeking an experienced MLOps Engineer to build, deploy, and manage scalable ML solutions for Roche's GIP platform.

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.

Experience: 5–8+ years in Python, ML engineering, and MLOps, preferably within life sciences or pharmaceutical R&D.