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Sujal Bais
Junior AI/ML Engineer specializing in applied machine learning and data pipelines
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About
Built and deployed an LLM-powered automation pipeline that ingests voice and documents, transcribes/extracts key information into structured data, and routes it through backend workflows using Python/FastAPI. Uses n8n to orchestrate multi-step AI processes with validation, retries, and monitoring, and iterates with stakeholders via rapid demos to refine changing requirements.
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Key Strengths
- Built and deployed production LLM system converting voice/doc inputs into structured data
- Designed reliability layers for unstructured inputs (preprocessing, strict output formats, validation checks)
- End-to-end orchestration of multi-step AI workflows with n8n (LLM calls, APIs, retries, error handling)
- Metrics-driven evaluation of AI workflows (accuracy, validation failure rate, latency, task completion rate)
- Iterative model/prompt strategy selection; added structured outputs and lightweight retrieval to improve consistency
- Effective collaboration with non-technical stakeholders via demos and incremental, testable delivery
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1 publication
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