Amazon Web Services (AWS), Automation, Best Practices, Cloud Computing, Computer Programming, Continuous Deployment/Delivery, Continuous Integration, Data Management, Data Modeling, Data Science, Database Extract Transform and Load (ETL), Distributed Computing, GitHub, Jenkins, Machine Learning, Microsoft Windows Azure, Performance Tuning/Optimization, Python Programming/Scripting Language, Systems Reliability
LOCATION
Santa Clara, CA
POSTED
30+ days ago
Role : MLOps Engineer Location : Scottsdale AZ (100% Onsite) Hire Type : Contract / Full time Rate : $65/hr / 130K No of roles - 7
MLOPs Engineer
SF_OP_204640-3-1
MLOPs Engineer
SF_OP_204640-3-2
MLOPs Engineer
SF_OP_204640-3-3
MLOPs Engineer
SF_OP_204640-6-1
MLOPs Engineer
SF_OP_204640-6-2
MLOPs Engineer
SF_OP_204640-6-3
MLOPs Engineer
SF_OP_204640-6-4
MLOps Engineer Role Overview 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