AI/ML Engineer_L51
Tasks
- Build and optimize ETL ELT pipelines for data ingestion feature engineering and transformation
- Build end to end ML pipelines for training validation deployment monitoring
- Create dashboards and analytics insights
- Design RAG pipelines and LLM integrations
- Design and implement ML and GenAI solutions
- Develop and deploy API-based AI applications
- Ensure scalable secure and cost optimized AI deployment
- Implement MLOps workflows for CI CD model registry experiment tracking retraining
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 profiling | Databricks | Dialogflow | Dialogflow ES | Docker | Document AI | Document Intelligence | ELT | ETL | FastAPI | Feature Engineering | Flask | Google Vertex | Google Vertex AI | Guardrails | JavaScript | Langchain | Langgraph | Looker | MLOps | Power BI | Prompt engineering | Python | QuickSight | RAG | SQL | Tableau | ThoughtSpot | Vector Search | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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