Data ML Ops Senior Engineer

• Collaborate with Data Scientists, AI Engineers, and Software Engineers to build robust ML pipelines.
• Automate deployment of ML models to production environments (CI/CD for ML).
• Implement model monitoring, logging, versioning, and lifecycle management.
• Optimize model performance and ensure reproducibility and scalability.
• Work with cloud platforms (AWS, GCP, or Azure) to manage compute resources and infrastructure.
• Integrate ML models into APIs or applications for real-time and batch inference.
• Apply best practices in MLOps: data validation, drift detection, testing, rollback strategies.
• Maintain ML metadata and experiment tracking systems.
• Ensure compliance with data privacy, security, and governance standards

Educational Requirements: Bachelor’s degree in computer science, Engineering, or a related field.
Required Industry Experience: Minimum 5 Years of Experience.
Technological Requirements: Very Good command of Microsoft Suites.
Language Requirements: Excellent command of English (spoken and written)