MLOps / LLMOps Engineer
INR 2500K-3100K (estimate) Senior-level Full Time
Tasks
- Apply tagging and cost tracking
- Automate CI/CD with GitHub Actions
- Build CI/CD pipelines
- Build and optimize LLM pipelines
- Deploy and manage ML/GenAI solutions
- Deploy reliable secure AI solutions
- Design and automate scalable ML/LLM systems
- Develop deployment workflows and tests
- Develop operational documentation disaster recovery
- Develop reusable templates and deployment patterns
- Enforce data residency and governance
- Ensure data contracts schema validation data quality
- Ensure governance and compliance
- Handle sensitive data security and obfuscation
- Implement alerting incident workflows
- Implement batch and real-time inference
- Implement model governance lineage access control
- Maintain high-performance AI systems
- Maintain lineage from data source to deployment
- Monitor pipeline health and model performance
- Operationalize model training evaluation deployment
- Optimize models with quantization caching
- Support budget and resource management
- Track LLM metrics including latency hallucination
Perks/Benefits
Skills/Tech-stack
AWS | Azure | CD pipelines | CI/CD | CI/CD pipelines | Cloud Platforms | Cost Optimization | Data Contracts | Data Processing | Data Quality | Data Quality Validation | Databricks | Delta Lake | Deployment Workflows | Disaster Recovery | Distributed data | Distributed data processing | Encryption | Enterprise analytics | FinOps | Geospatial Analytics | GitHub Actions | Infrastructure automation | ML deployment | ML deployment workflows | MLflow | Model Monitoring | Model Optimization | Model Serving | Observability | Power BI | Prompt engineering | Python | Quality validation | RAG Workflows | RBAC | SQL | Schema governance | Security | Unity Catalog | Vector Databases
Education
Roles
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