- 3+ years of experience in ML/AI engineering with demonstrable experience delivering production features.
- Understanding of the ML/AI lifecycle, including experimentation, evaluation, and release management.
- Experience with experiment tracking and model/version management concepts (tools such as MLflow are a plus).
- Hands-on experience with MLOps tooling (e.g., MLflow).
- Exposure to AI/agent frameworks (e.g., LangChain, LangSmith, CrewAI, Azure AI Agent Service, AWS Strands or similar).
- Experience with GenAI application development, including prompt iteration and agent/tool patterns.
- Familiarity with cloud platforms (AWS/Azure) and/or data platforms (e.g., Databricks).
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