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Varsha Hemakumar
Mid-level ML/AI Engineer specializing in NLP, RAG pipelines, and financial risk & fraud systems
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About
Built and shipped LLM/RAG systems in finance and startup settings, including a Goldman Sachs document intelligence platform that indexed ~8TB of regulatory filings and delivered cited, conversational answers with <2s latency—cutting compliance research by ~4.5 hours per batch. Also developed LangChain-based agent workflows at Finta to automate CRM enrichment and investor lookup with strong testing, tracing (LangSmith), privacy guardrails, and auditability.
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Key Strengths
- Built and deployed production RAG document intelligence platform on AWS SageMaker + Kubernetes
- Embedded and indexed ~8TB of regulatory filings into FAISS vector store
- Reduced compliance research time by ~4.5 hours per batch via conversational search with citations
- Systematic RAG tuning (chunk size/overlap) to improve relevance (~20%) while controlling token limits and hallucinations
- Low-latency optimization (kept query latency under ~2 seconds)
- Strong evaluation and reliability practices (unit tests, LangSmith tracing, guardrails, A/B testing, KPI-driven metrics)
- Experience collaborating with non-technical stakeholders on privacy, explainability, and adoption (audit logs, dashboards)
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