Senior MLOps Engineer
Bangalore - Karnataka - India
INR 3242K-4580K (estimate) Senior-level Full Time
Tasks
- Add guardrails and governance controls
- Automate data ingestion pipelines
- Build feature engineering workflows
- Build training pipelines
- Collaborate in technical reviews
- Design ML infrastructure
- Detect data drift
- Detect model drift
- Enable self service model deployment
- Ensure CI/CD readiness
- Implement logging and tracing
- Implement model packaging and deployment
- Implement observability
- Implement telemetry for ML pipelines
- Maintain dataset version control
- Maintain model cards
- Maintain model registry
- Mentor engineering teams on MLOps
- Optimize GPU inference
- Serve models with low latency
- Standardize AI development workflows
- Validate input data for ML systems
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | Airflow | Amazon SageMaker | Azure DevOps | B testing | CI/CD | CVAT | Containerization | DVC | Data Ingestion | Data Validation | Data labeling | DevOps | Drift Detection | Feature Engineering | Feature Store | GPU Inference | Git | Grafana | Inference endpoints | JFrog | Kubernetes | Logging | MLOps | MLflow | Machine Learning | Model Cards | Model Deployment | Model Governance | Model Monitoring | Model Registry | Model Training | N8n | Observability | OpenTelemetry | Sagemaker Pipelines | Shadow Deployment | Telemetry | Tracing | Version control
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