AI Engineer
Tasks
- Build and maintain MLOps infrastructure for model monitoring
- Clean and preprocess data for model training
- Collaborate with development teams for AI production deployment
- Design build deploy AI agents for operational workflows
- Design data ingestion pipelines
- Document models pipelines and prompts for auditability
- Document models pipelines and prompts for reproducibility
- Implement prompt chaining for knowledge aware automation
- Implement retrieval-augmented generation pipelines
- Integrate AI agents with enterprise systems via APIs
- Integrate AI agents with enterprise systems via database connections
- Preprocess data for model inference
Perks/Benefits
- N/A
Skills/Tech-stack
AI Agents | APIs | AWS SageMaker | Data Ingestion | Data Pipelines | Data Preprocessing | Data cleaning | Database Connectivity | Java | JavaScript | LLM integration | Language Models | Large Language Models | MLOps | Model Monitoring | Prompt Chaining | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | SQL | TensorFlow
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | MLOps Engineer | Machine Learning Engineer
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