MLOps Developer / Engineer

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

Job summary

Valiant Technologies LLC in South SFO, CA is seeking an experienced MLOps Developer/Engineer 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 AWS SageMaker, MLflow, Weights & Biases, and Docker experience; life sciences/pharma R&D exposure is preferred.

Qualifications

• 5-8+ years in Python, ML engineering, and MLOps.
• Experience with AWS SageMaker for model training, deployment, optimization, and monitoring.
• Preferably within life sciences or pharmaceutical R&D.
• Hands-on experience with MLflow and Weights & Biases for experiment tracking and model registry.

Responsibilities

• Build, deploy, and manage scalable ML solutions for Roche's GIP platform.
• Develop and maintain automated ML pipelines, CI/CD, monitoring, and retraining processes.
• Collaborate with data scientists and engineers to ensure reproducibility and data integrity.
• Integrate ML models into enterprise applications and ensure GxP compliance.

Skills

Python

ML engineering

MLOps

Life sciences

5-8+ years

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.