? We're Hiring: MLOps Engineer (10 Openings) ? Remote | ? 4–8 Years Experience | ? Immediate Joiners Preferred Key Responsibilities Design and manage end-to-end ML model deployment pipelines Work with Docker , CI/CD tools (GitLab, GitHub Actions), and Linux-based environments

Use Azure ML , AWS , or GCP for scalable training and deployment

Monitor production models using Grafana , Prometheus , and other observability tools

Manage container orchestration with Kubernetes (preferred)

Collaborate with Data Scientists to ensure seamless integration and deployment of ML models

Required Skills 4–8 years of overall experience in backend, DevOps, or MLOps

Solid knowledge of Git , Python scripting , and system automation

Experience with ML deployment , versioning, and performance optimization

Familiarity with cloud platforms and distributed systems

Ideal Profile Example 7 years in MLOps/backend engineering

Deployed TensorFlow and PyTorch models using Azure ML and GitLab CI/CD Set up real-time monitoring pipelines using Prometheus and Grafana Expertise in scripting, infrastructure scaling, alerting, and cost-performance tuning

📌 MLOps Engineer (Hyderabad)
🏢 Qloron
📍 Hyderabad