Applied AI/ML Scientist
Tasks
- Architect multi-agent workflows
- Collaborate with engineers to productionize agentic solutions
- Define evaluation frameworks for agent performance
- Design and build autonomous agentic systems
- Develop and integrate machine learning models
- Generate and execute analytical pipelines
- Implement testing monitoring versioning and iterative improvement
- Research agentic AI LLM orchestration and multi agent systems
- Translate logistics problems into agent formulations
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agent systems | Amazon Bedrock | Anomaly Detection | Anthropic API | Autogen | Azure | CI/CD | Cross-validation | Data Drift | Data Drift Detection | Deep learning | Demand forecasting | Docker | Drift Detection | Error Analysis | GCP | Kubernetes | LLM orchestration | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Multi-Agent | Multi-Agent Systems | OpenAI API | Prompt engineering | Python | Spark
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