MLOps Engineer - Cloud Infrastructure

Role Overview :

As an MLOps Engineer, you will be responsible for bridging the gap between machine learning development and production deployment. You will work closely with data scientists, ML engineers, and IT operations to ensure that ML models are deployed, monitored, and scaled effectively.

This role involves both technical skills in cloud infrastructure, CI / CD, and DevOps, as well as an understanding of the full machine learning lifecycle

Key Responsibilities :

• Model Deployment : Design, develop, and implement CI / CD pipelines for automating the deployment of machine learning models to production environments.
• Model Monitoring & Management : Build tools to monitor model performance in real-time and trigger automatic re-training when model drift occurs. Ensure models are scalable and optimized for high-performance.
• Collaboration : Work closely with data scientists and ML engineers to ensure smooth integration of ML models into production, focusing on reliability and scalability.
• Automation : Automate model training, deployment, and lifecycle management processes to improve efficiency and reduce manual overhead.
• Cloud & Infrastructure Management : Manage cloud resources (AWS, GCP, Azure) and infrastructure to ensure high availability, cost optimization, and efficient scaling of ML workloads.
• Versioning & Experiment Tracking : Implement versioning systems for model artifacts, datasets, and training environments. Track experiments and ensure reproducibility.
• Security & Compliance : Ensure that the deployed models meet security and regulatory requirements (data privacy, model governance, etc.).
• Troubleshooting & Optimization : Debug and troubleshoot production ML models, and optimize performance issues related to compute, data pipelines, and model inference.

Required Qualifications :

Education : Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field.

Experience :

Technical Skills :

Preferred Qualifications :

(ref : hirist.tech)