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Salil Khandelwal

@salilkhandelwal

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I build and deploy scalable ML systems, LLM applications, RAG pipelines, and agent workflows.

Canada

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What I'm looking for

I'm looking to build and deploy production AI systems that turn ambiguous business problems into measurable outcomes, especially across LLM applications, RAG pipelines, agent workflows, ML evaluation, and scalable model-serving systems.

I've built and deployed production ML and AI systems at Microsoft, including an LLM-driven escalation system using RAG, prompt engineering, and LangGraph to route customer interactions at scale.

I also developed voice-authentication fraud detection systems, adapting and calibrating models with client-specific data to reduce false alerts by 50% while maintaining 90% true positive rates.

Previously at Nuance Communications, I developed NLU data augmentation techniques that reduced data collection effort by 90%, and built topic-modeling solutions that reduced optimization turnaround time by 83% and contact center traffic by 40%.

My experience also includes data science roles at Shopify and Expedia Group, where I analyzed customer workflows, chat systems, search, and transaction data to improve scalable analytics, customer experience, ranking, and recommendation systems.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist II

Current

Microsoft

Mar 2022 - Present (4 years 7 months)

Built and deployed an LLM-driven escalation system using RAG, prompt engineering, and workflow orchestration (LangGraph), enabling automated routing of customer interactions at scale in production environments. Built and deployed ML systems for voice authentication in fraud detection, improving performance under changing data conditions in production environments.