Sunil Ravilla
Generative AI Engineer @ Hewlett Packard Enterprise
About
From launching satellites at ISRO to deploying LLMs at HPE — I've spent my career building systems where failure isn't an option. Today I build production-grade Generative AI systems at Hewlett Packard Enterprise, working across RAG architectures, LLM fine-tuning, AI agents, and evaluation frameworks. My path: IIT Indore → NTU Singapore → ISRO → Georgia Tech → HPE What I bring to the table: → End-to-end ML/AI system design and production deployment → LLM evaluation, LLM-as-a-judge frameworks, and quality assurance for GenAI → RAG pipelines, fine-tuning, and prompt engineering at enterprise scale → AI on HPC infrastructure — where compute constraints force creative solutions → Cross-domain thinking from aerospace engineering to enterprise AI I write about practical GenAI lessons here on LinkedIn — what actually works in production, not what looks good in a demo. 📩 Open to: Speaking, consulting, and collaboration on AI projects
United States
Sunnyvale
Computer Software
Stable Diffusion, Automatic Speech Recognition, Trustworthy AI, LLMS, Retrieval-Augmented Generation (RAG), Multimodal, LLMs, Agentic AI, Advanced RAG, Pachyderm, Determined.ai, Kserve, XGBoost, Random Forest, Containerization, Speech Recognition, Text-to-Speech Synthesis, Chatbot Development, NeMo, Riva
Experience

Data Science Consultant
Atlanta, Georgia, United States
• Leveraged data from millions of active Cox Communications devices to promptly identify firmware-related issues within one hour of updates, conducting thorough analysis and visualization for actionable insights • Developed Random Forest and XGBoost models to swiftly identify firmware and power-related failures within a specific CPE device family, achieving a 68 % AUC. Employed Tableau to visualize the model’s predictive performance trends for better insights

Scientist Engineer 'SC'
• Data analysis software: Automated critical test data analysis procedures by developing a python driven application resulting in reduction of time required for analysis, from over 36 hrs. to 30 min (70x faster) • Data visualisation tool: Built a dashboard for real time data analysis and visualisation of results from ground-level flow tests to aid in early detection of anomalous behavior in flight subsystems • Product Development: Analysed 25+ features such as Pressure, Temperature, etc., from ground-level tests to recommend design and development upgrades for an indigenously developed Cryogenic Upper Stage Engine • Failure Analysis: Executed a comprehensive Root Cause Analysis to determine causes of anomalies in GSLV F10 Launch Vehicle; Saved $1.2M by performing extensive exploratory data analysis to understand trigger points • Medical Ventilators: Designed cost-effective blower-based ventilator, reducing cost by 85% with locally sourced components. Assisted in knowledge transfer of designs to over 15 public sector and government organizations

Research Intern
Developed a mathematical model to estimate with 92% accuracy the drug delivery rate from Polyampholyte-based Hydrogels. Performed sensitivity analysis and carried out parameter optimisation using metaheuristic algorithms
Education
Sunil Ravilla's Contact Information
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