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MLOps Developer / Engineer

Robotics Technologies · CA, US

Spotted 37m ago

Job details

Level
Senior
Experience
5+ years
Posted
Nov 13, 2026
Last confirmed open
Nov 13, 2026
Job function
Software/Internet/AI › Machine Learning & AI › Machine Learning, Operations (ML Ops)
Job description

About this role

  • 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

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.

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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