MLOps Engineer

Role : MLOPS Engineer

Location :
Scottsdale AZ (Onsite)

Work mode :

- Onsite Hybrid 3 days a week

Exp :: 11+ years

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.

• 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 product ionizing 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

• Strong programming skills in Python
• Experience with ML frameworks:
  Tensor Flow, PyTorch, Scikit-learn
• Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, Sage Maker, Azure ML
• Knowledge of CI/CD tools:
  Jenkins, Git Hub Actions, Git Lab CI
• Experience with cloud platforms: AWS
• Strong understanding of data pipelines, ETL processes, and distributed systems