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Vinay Ramrupe
Mid-level AI/ML Engineer specializing in LLM and enterprise generative AI
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About
ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.
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Key Strengths
- End-to-end ownership of production ML/LLM systems
- LLM platform and enterprise copilot experience
- RAG-based enterprise knowledge retrieval design
- Strong productionization focus for AI systems
- Inference and serving optimization
- Balanced latency, throughput, cost, quality, and safety tradeoffs
- Automated model evaluation and regression detection
- Safety guardrails for enterprise GenAI applications
- Python platform/tooling design for internal engineering teams
- Scalable data pipeline development with Spark and Delta Lake
- Experimentation rigor with PyTorch and MLflow
- Improved throughput by 20%
- Reduced manual evaluation effort by 30%
- Improved team consistency and reliability through shared tooling
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