About
With 13 years of pioneering experience in AI, including a decade dedicated to engineering production-grade AI systems, I specialize in Deep Reinforcement Learning and Generative AI/LLM models. My expertise has driven product innovations in marketing automation and consumer applications, earning recognition as a '40 under 40 Data Scientist'. Seeking to leverage deep technical leadership and entrepreneurial drive to build cutting-edge AI solutions.
Work
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Summary
As Co-founder, CTO & AI Lead, I spearheaded the development of a low-code AI-powered gamification platform to enhance engagement in consumer applications, leading a team of 25+ engineers.
Highlights
Architected and deployed an end-to-end Gen AI pipeline utilizing LangChain & RAGs, integrating LLMs/GPT-4 to generate dynamic gamification campaigns.
Engineered a high-volume Data platform on AWS, processing over 1 billion events monthly with scalable backend APIs serving millions of users at <200ms latency.
Led and mentored a cross-functional team of 25+ engineers, successfully launching multiple AI products that significantly drove user engagement.
Developed a multi-modal platform to support diverse gamification campaigns, enhancing user experience and retention.
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Summary
As Co-founder and AI Lead, I developed an AI-powered user churn reduction platform for B2C companies, focusing on advanced machine learning and deep learning solutions.
Highlights
Developed a marketing copy generation engine by fine-tuning GPT-2, optimizing promotional content and improving campaign effectiveness.
Built a user behavior prediction platform leveraging event-based Recurrent Neural Networks, Auto-Encoders, and Latent space clustering to identify churn risks.
Engineered a Deep Reinforcement Learning-based action recommendation system, simulating a promotions marketing environment to train models for churn prevention.
Implemented product recommendations using hybrid neural collaborative filtering and content filtering, deploying AI models and Backend APIs on Microsoft Azure stack.
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Summary
As Founder and CEO, I launched an AI-driven startup disrupting food recommendations, securing funding from Tim Draper (DFJ) and developing innovative solutions.
Highlights
Built a mood-based restaurant and dish recommendation engine utilizing the NLTK library, enhancing personalized user experiences.
Utilized crowdsourcing techniques for labeled data collection on mood and food preferences, building a robust dataset for AI model training.
Secured early-stage funding from Tim Draper (DFJ), validating the business model and market potential of the AI-powered food recommendation platform.
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Summary
As an Associate at IIHS, I contributed to an Innovation University focused on sustainable urban development by incubating AI startups and providing technical and architectural guidance.
Highlights
Incubated multiple AI startups, providing strategic guidance and technical support to foster innovation in sustainable urban development.
Provided expert technical and AI architecture guidance to various startups, enabling them to build robust and scalable solutions.
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Summary
As a Technical Program Manager, I managed seed fund operations for technology startups in India, focusing on dealflow creation and technical due diligence.
Highlights
Created a robust dealflow of over 30 high-quality AI startups, identifying promising investment opportunities for the seed fund.
Identified the top 5 investment opportunities through comprehensive technical analysis and due-diligence, informing strategic investment decisions.
Education
Awards
Techstars Accelerator Selection
Awarded By
Techstars
AI startup CustomerGlu was selected for the prestigious Techstars accelerator in 2021, validating its innovation and market potential.
40 under 40 Data Scientist
Awarded By
Analytics India Magazine
Recognized as a top Data Scientist by Analytics India Magazine in 2019 for significant contributions to the field.
Publications
Languages
English
Skills
Generative AI
GPT-4, HuggingFace, LangChain, RAGs, Pinecone, PEFT, Diffusion Models.
Deep Learning
RNNs, CNNs, Transformers, AutoEncoders, PyTorch, Tensorflow.
Machine Learning Operations (MLOps)
AWS SageMaker, Azure ML, MLFlow.
Data Engineering
Kinesis, Redshift, BigQuery, Cassandra, Databricks, Airflow, Spark.
Backend & Cloud
NodeJs, Python, GoLang, Docker, Mongo, Redis, AWS, Azure.
Natural Language Processing (NLP)
NLTK.
Statistical Analysis
Linear Algebra, Calculus, Probability, Statistics.
Programming Languages
Python, C++.
System Architecture
Computer Architecture & Organization, Automation, Optimization.