AI/ML Engineer_MS
Tasks
- Build API based AI applications
- Build ETL/ELT pipelines
- Build dashboards and analytical insights
- Deploy and monitor ML models
- Design RAG pipelines
- Design and implement ML and GenAI solutions
- Develop end-to-end ML pipelines
- Ensure scalable secure cost optimized deployments
- Implement MLOps workflows with CI CD
- Implement prompt engineering and evaluation
- Integrate LLM applications
Perks/Benefits
- N/A
Skills/Tech-stack
AI Foundry | AI Search | AWS Bedrock | App Service | Azure AI | Azure AI Foundry | Azure AI Search | Azure App | Azure App Service | Azure Bot | Azure Bot Service | Azure Data | Azure Data Factory | Azure Document Intelligence | Azure OpenAI | Azure Synapse | BigQuery | Blob Storage | CI/CD | Cloud Run | Cloud Storage | Data Factory | Data Ingestion | Data Lineage | Data Quality | Databricks | Dialogflow | Dialogflow CX | Docker | Document Intelligence | ELT | ETL | Embeddings | Experiment tracking | FastAPI | Feature Engineering | Flask | Google Cloud | Google Cloud Storage | Google Vertex | Google Vertex AI | JavaScript | Langchain | Langgraph | Looker | MLOps | Model Registry | Observability | Plotly Dash | Power BI | Prompt engineering | Python | QuickSight | RAG | SQL | Tableau | ThoughtSpot | Vector Search | Vertex AI
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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