MLOps Developer / Engineer

Robotic Process Automation LLC; California; On-site; USD 86,000 - 123,000; Full time

Job summary

Roche seeks an experienced MLOps Engineer to build, deploy, and manage scalable ML solutions for the GIP platform in a fast-paced life sciences setting.

You have 5–8+ years in Python, ML engineering, and MLOps, with hands-on AWS SageMaker, MLflow, W&B, and Docker, and you will collaborate with data scientists and engineers on production deployments.

On-site in South SFO, CA for an 8-month contract, with W-2/1099/C2C options.

Qualifications

• 5–8+ years in Python, ML engineering, and MLOps.
• Experience deploying ML models to prod in enterprise environments.
• Life sciences or pharmaceutical R&D experience preferred.

Responsibilities

• Build, deploy, and manage scalable ML solutions for Roche's GIP platform.
• Develop automated ML pipelines, CI/CD, model monitoring, drift detection, and retraining.
• Collaborate with data scientists and engineers to integrate models into enterprise applications.
• Ensure model explainability and compliance with GxP requirements.

Skills

Python programming

XGBoost

Predictive analytics

Churn modeling

ML engineering

MLOps

CI/CD

Model monitoring

GxP compliance

Tools

AWS SageMaker

MLflow

Weights & Biases

Docker

Git

AWS S3

HPE Swarm Learning

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: MLOps Developer / Engineer

Location: South SFO, CA

Duration: 8 Months + Extension

Bill Rate: $76/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description

MLOps Skills

• We are seeking an experienced MLOps Engineer to build, deploy, and manage scalable ML solutions for Roche's GIP platform.
• 5-8+ years in Python, ML engineering, and MLOps,
• Preferably within life sciences or pharmaceutical R&D.

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.
• Integrating ML models into enterprise applications.
• 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.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.