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Tulasi padamata
Junior Machine Learning Engineer specializing in Document AI and LLM-powered workflows
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About
Built and owned a customer-facing Document Intelligence Service for legal contract analytics at Noasis Digital, delivering extraction/summarization with careful accuracy controls (confidence thresholds, versioned deployments, production logging). Also developed a React/TypeScript document review app and internal QA dashboard, and has hands-on microservices experience with async messaging (RabbitMQ), timeout tuning, and centralized structured logging for reliability at scale.
Experience
Education
Key Strengths
- Owned end-to-end customer-facing ML/document intelligence pipeline (model selection through deployment and monitoring)
- Balances speed vs. quality in high-stakes legal document workflows using confidence thresholds and controlled rollouts
- Rapid iteration via baseline-first approach and early internal API deployment for limited user testing
- Designs scalable React/TypeScript systems with strict API contracts and shared types to reduce integration bugs
- Microservices reliability at scale (handles message duplication/service failures with timeouts and centralized structured logging)
- Builds internal dashboards that improve analyst/engineer workflows by centralizing outputs, confidence scores, and failure cases
- Strong user-feedback loop: shadowing users, frequent small releases, prioritization by measurable impact (time saved, error reduction, adoption)
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