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Abhiram Mullapudi
Mid-level ML Engineer specializing in real-time inference and anomaly detection
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About
Built DocMind, an end-to-end PDF chat assistant using React/TypeScript, FastAPI, and Postgres/pgvector, showing full-stack ownership plus practical performance tuning and AWS debugging skills. At Social Tech Labs, improved onboarding, shipped lean under ambiguity, and created a reusable low-latency feature serving layer that reduced duplicated infrastructure work across models.
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Key Strengths
- End-to-end product ownership across frontend, backend, and database layers
- Cross-layer debugging and infrastructure diagnosis
- Performance tuning for retrieval-based applications
- Pragmatic onboarding and activation improvements
- User-centered UX iteration informed by support tickets and observation
- Strong MVP judgment under ambiguity
- Reusable platform/API design for repeated product patterns
- Balances abstraction with model-specific flexibility
- Multi-tenant data isolation and validation guardrails
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