Role : MLOPS Engineer Location : Scottsdale AZ (Onsite) Rate : $62 No of roles : 3 Indents :
SF_OP_204640-3-1
SF_OP_204640-3-2
SF_OP_204640-3-3
We are looking for a skilled MLOps Engineer to design, deploy, and manage scalable machine learning pipelines in production. The role focuses on enabling seamless integration of ML models into enterprise systems with reliability, automation, and governance.
Key Responsibilities
Design and implement end-to-end ML pipelines from data ingestion to model deployment
Build and manage CI/CD pipelines for ML models (training, testing, deployment)
Automate model monitoring, retraining, and performance optimization
Collaborate with Data Scientists and Data Engineers for productionizing ML models
Ensure scalability, reliability, and security of ML systems
Manage model versioning, experiment tracking, and lifecycle management
Implement best practices for governance, compliance, and reproducibility
Key Skills & Expertise
Strong programming skills in Python
Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML
Knowledge of CI/CD tools: Jenkins, GitHub Actions, GitLab CI
Experience with cloud platforms: AWS
Strong understanding of data pipelines, ETL processes, and distributed systems
Numbers & Facts
Location
Santa Clara, CA
Skills
Amazon Web Services (AWS)unmatched
Automationunmatched
Best Practicesunmatched
Cloud Computingunmatched
Computer Programmingunmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
Data Managementunmatched
Data Modelingunmatched
Data Scienceunmatched
Database Extract Transform and Load (ETL)unmatched
Distributed Computingunmatched
GitHubunmatched
Jenkinsunmatched
Machine Learningunmatched
Microsoft Windows Azureunmatched
Performance Tuning/Optimizationunmatched
Python Programming/Scripting Languageunmatched
Systems Reliabilityunmatched
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