Umang Wani
Applied ML Engineer |🚀 Leading ML at SalesDNA.ai |🧠LLMs, Text-to-SQL, MLOps |💼 Building AI-Powered Sales Intelligence Platforms
- Role
- Machine Learning Engineer at Salesdna.Ai
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Umang Wani
As a Machine Learning Engineer and Data Scientist at SalesDNA.ai, I lead the development…
Experience
Machine Learning Engineer
Jun 2023 — Present · Seattle, WA, US
Currently leading machine learning initiatives at SalesDNA.ai, with a focus on building scalable, production-grade ML and GenAI systems that deliver real-time insights to end users- Designing and deploying machine learning models that generate actionable insights for end customers about their sales team performance. Leveraging historical data, behavioral patterns, and predictive analytics to surface trends, highlight risks, and empower sales leaders to make data-driven decisions- Enhancing customer experience by developing tailored ML-driven insights, performance matrices, and dashboards that help end users evaluate sales team effectiveness. Delivered clear, actionable analytics—such as rep benchmarking, pipeline health, and forecast reliability—empowering customers to make confident, data-informed decisions- Facilitating cross-functional collaboration by partnering with data engineers, UI/UX designers, and full-stack developers to ensure end-to-end integration of ML features—from data pipelines to model deployment and front-end visualization. Played a key role in aligning business goals with technical execution, accelerating product development cycles and improving system reliability- Innovating with AI and GenAI, leading the integration of large language models (LLMs) through Retrieval-Augmented Generation (RAG) workflows for Text-to-SQL use cases using Amazon Bedrock and other LLM platforms. Continuously advanced product capabilities, enabling natural language data querying and delivering intelligent, scalable insights.
Education
Maharashtra Institute of Technology
Bachelor of Engineering
2014 — 2018
Carnegie Mellon University
Master's degree
2021 — 2022
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