Pavan Prasanna Kumar

ID.me is a leading AI-powered digital identity platform serving over 160 million users across 20 federal agencies, 44 state agencies, and 66 healthcare organizations, enabling secure, streamlined identity verification, and seamless access to online services.

• Directed 35-person cross-functional team, developing mobile and web wallets, driving revenue growth in government and healthcare sectors.
• Executed a strategic product vision for ID.me's identity platform, contributing to a company valuation exceeding $2B.
• Launched national-scale Identity Wallet for over 160 million users while ensuring compliance with federal regulations.
• Built scalable identity platform with APIs and SDKs, generating over $20 million in new revenue streams.
• Led data architecture migration from SQL to GraphQL, enhancing real-time personalization and transaction processing capabilities.
• Optimized platform economics through vendor contract renegotiation and technology stack refinement, improving cost structure.
• Deployed AI-powered identity verification using fine-tuned LLMs with RAG architecture, boosting customer support efficiency, and reducing verification time from 8 days to 5 minutes.
• Navigated complex federal regulations to secure identity verification at IRS and TSA airport terminals nationwide.

Here are refined resume points:

• Led a cross-functional team of 30+ members, including 2 product managers, to enhance the Facebook Feed recommendation engine (RecSys) for over 3 billion users, increasing daily active users by 20 million and average feed time by 4 minutes.
• Defined a long-term RecSys product strategy, balancing content integrity, user engagement, and ecosystem value across creators and consumers.
• Designed an ecosystem-aware reinforcement learning framework to optimize content relevance and diversity, improving the experience for both creators and users.
• Developed distilled LLMs for advanced content understanding and user behavior analysis, significantly improving post recommendation accuracy.
• Launched the Facebook Explore feature, targeting youth audiences through LLaMA-based classifiers and refined UX design, expanding platform reach.
• Strengthened feed integrity by building ML models that reduced harmful content exposure by approximately 5% and improved misinformation detection and filtering, especially during the U.S. election period.
• Implemented trust and safety enhancements during critical election and crisis periods, increasing user trust, while maintaining engagement levels.

• Oversaw product strategy and P&L for $30M+ ARR AWS AI computer vision products focused on identity verification, leading a cross-functional team of over 40 members across PM, Science, Engineering, Data Ops, and UX.
• Launched flagship Face Liveness product, generating $4M ARR in year one by managing pricing, go-to-market strategy, launch narrative, and fairness initiatives.
• Architected core capabilities for Amazon Bedrock, including LangChain structure and vector database integration, while facilitating onboarding of Anthropic’s initial models.
• Introduced video-to-text LLMs to enhance video understanding and search Q&A, spearheading model evaluation, prompt fine-tuning, and A/B testing to broaden CV applications.
• Rationalized Vision API portfolio by leading deprecation of underperforming APIs, negotiating customer transitions, and consolidating offerings to improve portfolio health and reduce costs.
• Drove global go-to-market strategy for AWS identity verification suite—Voice ID, Face ID, Fraud Detector—enhancing Trust & Safety adoption across various Amazon businesses.
• Advanced edge-based computer vision strategy by expanding support for new workloads and executing regional AWS launches with comprehensive GTM planning and pricing strategies.
• Championed deployment of AI solutions within identity verification domain to foster innovation and operational efficiency.

• Directed App Store product management to enhance payments for 1P and 3P apps, decreasing involuntary churn and boosting transaction success with ML-driven predictions, generating over $100M in annual impact.
• Launched global Flexible Grace Period feature for developers, driving widespread adoption among 2M+ app developers through A/B testing and collaboration with top developers in 150+ countries.
• Introduced two-click checkout with ML-based risk assessment, tripling conversion rates compared to legacy three-step flow and accelerating transaction speed.
• Led development of KPI-centric analytics suite, increasing dashboard engagement by 40% and enabling developers to optimize subscription performance.
• Negotiated with global payment networks to reduce transaction costs, enhancing App Store unit economics.

• Managed team of five quants to develop ML-based valuation and risk models for $20B in interest rate derivatives, improving pricing accuracy for $80B in daily trades, generating over $30M in annual impact.
• Established Interest Rates Quant Team in India, overseeing recruitment, onsite training, and career development for up to eight members.

• Developed ML predictive tools and cross-regional trading systems, generating $5M in annual profit.
• Led large-scale data migration from Sybase 12 to 15, achieving 28 percent faster processing without any downtime.