Build and productionize classification and extraction models that power AI agents and semantic data systems, while converting large-scale unstructured data into structured signals for downstream AI.
HG Insights is the pioneer of Revenue Growth Intelligence. For more than a decade, we have delivered comprehensive, AI-driven datasets on B2B buyers, technology adoption, IT spend, and buyer intent, sourced from billions of data points. Today, we are a trusted partner to Fortune 500 technology companies, hyperscalers, and innovative B2B vendors seeking precise go-to-market analytics and decision-making.
Through an evolving suite of AI agents that incorporate first-party data and buyer signals, HG Insights enables AI-powered GTM automation across sales, marketing, RevOps, and data analytics teams, modernizing GTM execution from strategy through activation.
We are looking for an Applied Data Scientist to build and productionize classification and extraction models that power AI agents and semantic data systems. This role focuses on converting large-scale unstructured data into high-quality structured signals that feed semantic layers, knowledge graphs, and downstream AI workflows.
The role works closely with AI engineering and platform teams and owns the ML lifecycle from problem framing and dataset design to model deployment and quality monitoring. This is a hands-on role with strong emphasis on practical ML systems, not academic research or dashboard analytics.
Key Skills:
These are exactly right for your Applied DS / AI-agent role:
Tools (Expected)
Working knowledge
Nice to have
Ready to build the future of AI infrastructure? Apply now to join HG Insights as a Staff/Senior Machine Learning Engineer in Pune.
HG Insights delivers AI-driven datasets that provide deep insights into B2B buyers and technology adoption, specifically tailored for enterprise customers. Their platform empowers businesses to make informed go-to-market decisions and optimize their marketing and sales strategies, while redefining product marketing through an AI-first approach.
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