MLOps Developer / Engineer

Quantum Technologies. LLC; California; On-site; USD 86,000 - 123,000; Full time

Job summary

Quantum Technologies. LLC is seeking an experienced MLOps Developer/Engineer in the South SFO, CA area to build, deploy, and manage scalable ML solutions for Roche's GIP platform.

The role requires 5-8+ years in Python, ML engineering, and MLOps, with strong experience in AWS SageMaker, MLflow, and W&B. We expect hands-on Python development, experience with Docker and CI/CD, and familiarity with distributed training approaches.

Qualifications

• 5-8+ years in Python, ML engineering, and MLOps.
• Experience with SageMaker for model training, deployment and monitoring.
• Familiarity with MLflow and W&B for experiment tracking and model registry.
• Knowledge of privacy-preserving distributed training (e.g., Swarm Learning) is a plus.
• Experience deploying ML in enterprise applications with CI/CD pipelines.

Responsibilities

• Build, deploy, and manage scalable ML solutions for Roche's GIP platform.
• Develop automated ML pipelines and CI/CD workflows.
• Monitor model performance, drift, and retraining processes.
• Collaborate with data scientists and engineers to integrate models into enterprise apps.

Skills

Python

ML engineering

MLOps

AWS SageMaker

XGBoost

Docker

CI/CD

Weights & Biases

Tools

MLflow

Weights & Biases (W&B)

AWS S3

Git

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.