Role Overview

The MLOps is responsible for building and maintaining the full machine learning lifecycle across cloud and on-prem environments. This includes integrating data pipelines, labeling flows, training pipelines, testing frameworks, model optimization, deployment to cloud and embedded hardware, and monitoring of model performance. The role works closely with AI Engineers, Framework Engineers, Application Engineers, Data Engineering, and Label Management to enable scalable, reliable, and production-ready ML systems for autonomous driving.

Key Responsibilities

End-to-End MLOps Pipeline Development
- Build and maintain automated end-to-end ML pipelines covering data ingestion, dataset management, labeling workflows, training, validation, optimization, deployment, and monitoring.
- Ensure ML pipelines run in both cloud and on-prem GPU clusters, with solid reproducibility and traceability.

Data & Labeling Integration
- Integrate data pipelines with labeling platforms and automate dataset creation and quality checks.




- Work closely with the Label Manager to enforce labeling quality gates and track dataset KPIs.

Model Deployment
- Establish deployment pipelines for ML models to:
- Cloud platforms (Azure/AWS)
- On-prem HPC/GPU clusters (Kubernetes, Slurm, NVIDIA infrastructure)
- Embedded compute platforms (NVIDIA Orin)

Monitoring & Observability
- Develop automated monitoring systems for model drift, data drift, performance degradation, anomalies, and operational metrics.
- Build dashboards and alerts to monitor model performance across simulation and on-vehicle tests.

Collaboration & Cross-Functional Alignment
- Work closely with:
- AI Engineers on training and evaluation
- Framework Engineers on model optimization
- Application Engineers integrating ML outputs into the autonomy stack
- Data Engineering on scalable data and storage architecture
- ML Architect on integration and implementation of new components
- Drive best practices for MLOps, documentatio

📌 Senior / Lead MLOps Engineer - Multiple Locations (Hyderabad)
🏢 EPAM Systems
📍 Hyderabad