Dec 2021 – Dec 2022 · 1 yr · Hyderabad, Telangana, India · Hybrid

• Delivered two research-driven ML solutions for molecular property prediction—boosting performance by 2–4× and unlocking $8M+ in expansion ARR ($2.2M upsell, $5.8M consulting), positioning the platform as a market leader in computational drug discovery.
• Scaled product innovation across nearly half the software suite by translating cutting-edge ML research into intuitive, production-ready features in collaboration with scientists. Unlocked executive investment by reframing technical roadmaps into ROI-focused business cases.
• Led end-to-end integration of two predictive ML models into the flagship web/desktop applications–foundational to 46% of the company’s product portfolio. Orchestrated execution of foundational upgrades across 10+ product teams, navigating complex and interdependent data pipelines across platforms.
• Drove a 34% reduction in critical bug reports and accelerated delivery of high-impact features by embedding customer feedback into roadmap prioritization, improving product quality and customer satisfaction.

Mar 2019 – Nov 2021 · 2 yrs 8 mos

• Co-directed multi-year product vision and shaped execution for three core products (30%+ annual revenue contribution), leading a 20-member cross-functional team (Engineering, ML, Data Science, Research, MLOps, UX). Successfully embedded ML strategy into complex, cross-platform products by securing executive sponsorship and aligning global stakeholders.
• Enabled over $7M in first-year expansion ARR from 4 Fortune 500 pharma partners by boosting user activation by 39% and adoption by 44% through targeted UX improvements and 6+ API integrations.
• Reduced modeling cycles from months to hours by launching a GPU-enabled AutoML tool, democratizing ML access for thousands of pharma scientists via intuitive web interfaces.
• Revamped backend architecture and UI to integrate 13+ deep learning models (GCNNs, XGBoost, Random Forest Ensembles) into a fully automated ML pipeline. This dramatically increased ML feature velocity, enabling rapid prototyping, parallelized training of 200+ models per run and deployment via Kubeflow on AWS.
• Co-delivered extensible ML infrastructure that later powered 6+ high-impact ML products by partnering with engineering, significantly reducing development cycles and enabling scalable cloud deployments for new AI features.
• Enhanced user trust and auditability of 200+ production models by co-delivering a 0→1 ML Monitoring Dashboard with Explainable AI (adding feature importance & uncertainty estimation). I also drove an API-first integration strategy and design.

Jul 2018 – Feb 2019 · 7 mos

Aug 2016 – Jun 2018 · 1 yr 10 mos

Sep 2015 – Oct 2015 · 1 mo · Greater Delhi Area · On-site

• Hands on training in these disciplines:
• High Performance Scientific Computing
• Drug Design & Discovery
• Protein Folding
• Genome analysis

Jun 2015 – Jul 2015 · 1 mo · Computational Biophysics and Soft Matter Research Group · On-site

• Research Project: "Quantification of hydrophobic interactions of aggregates of small amino acids in a variety of solvents by Molecular Dynamic Simulations".