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Sharath Kumar
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
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AI/ML engineer with HP experience building and productionizing an LLM-powered document intelligence platform (LangChain + Pinecone) to deliver semantic search and contextual Q&A across millions of enterprise support documents. Demonstrates strong MLOps and scaling expertise (Airflow, Kubernetes autoscaling, Triton GPU inference, monitoring with Prometheus/W&B) plus a structured approach to evaluation (A/B tests, shadow deployments, failover) and effective collaboration with non-technical stakeholders.
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Key Strengths
- Built and deployed production LLM document intelligence system for enterprise support search at HP
- Scaled semantic search/Q&A over millions of documents with vector DB + embedding caching
- Performance optimization across retrieval and inference (batched requests, index tuning, Triton GPU serving, Kubernetes autoscaling)
- Strong MLOps/orchestration experience (Airflow, Kubernetes, CI/CD with GitHub Actions and Azure DevOps)
- Reliability-focused evaluation approach (unit/integration/e2e/regression tests, monitoring, A/B tests, shadow deployments, failover)
- Able to translate non-technical stakeholder needs into measurable technical requirements and iterate via prototypes/feedback
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