MLOps Developer / Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Taft (CA); On-site; USD 83,000 - 138,000; Full time

Job summary

Machine Learning Technologies LLC is seeking an experienced MLOps Developer/Engineer to design, deploy, and manage scalable ML solutions for Roche's GIP platform in a California location. The role covers training, deployment, optimization, and monitoring of models using AWS SageMaker, MLflow, and W&B.

Strong Python and collaboration with data scientists are required to ensure robust, compliant production pipelines.

Qualifications

• 5–8+ years in Python, ML engineering, and MLOps.
• Preferably within life sciences or pharmaceutical R&D.
• Strong Python programming with hands‑on experience in XGBoost, predictive analytics, and churn modeling.
• Experience with Docker, AWS S3, Git, and integrating ML models into enterprise applications.

Responsibilities

• Build, deploy, and manage scalable ML solutions.
• Train, deploy, optimize, and monitor models using AWS SageMaker.
• Track experiments with MLflow and Weights & Biases.
• Implement automated ML pipelines, CI/CD, monitoring, drift detection, and retraining.

Skills

Python

XGBoost

Predictive analytics

Churn modeling

HPE Swarm Learning

Tools

AWS SageMaker

MLflow

Weights & Biases

Docker

AWS S3

Git

Job description

Job Details

Job ID: J55271

Job Title: MLOps Developer / Engineer

Location: South SFO, CA

Duration: 8 Months + Extension

Domain Exposure: Aerospace/ Airlines

Client: To Be Discussed Later

Employment Type: W-2, 1099, C2C

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

Bill Rate: $76/hour (C2C)

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.

Equal Opportunity Employer

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.

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