Director AI Solutions Engineering

I bridge AI strategy with hands-on engineering to build scalable AI-native business units & ventures. I work closely with early-stage teams to define where AI drives value, design the technical blueprint, and bring AI products to life

Cofounder + Coach/Consultant

ADSP Data Science Mentor

- Mentor for the Applied Data Science Program offered by Massachusetts Institute of technology ( MIT) - Mentored more than 600+ industry professionals for 250+ hours with an average top review score of 4.81/5 - Coached industry professionals with hands-on case studies on different ML topics ranging from Python for Data Science to Recommendations and CNN algorithms

Senior Machine Learning Engineer

- Led the development of the machine learning strategy and roadmap as the first ML hire of the company and grew the team from 1 to 5 members in 2 years. Owned multiple components of ML Projects building product criteria, scoping, resource allocation, deliverable timelines, tech documentation, using SOTA algorithms. - Built a prototype that utilizes transformer-based BERT models and newsletter scraping to extract funding data resulting in 30K data points from five newsletters. Formulated metrics for data quality for 1B data points to help improve accuracy of models. - Built an LLM-Powered ML pipeline to create an AI assistant to help venture capitalists get information about startups to invest in. - Spearhead the development of an in-house ML Product for entity resolution, a core capability of the product, by building an auto labeling tool using LLM in a sprint. - Interviewed 30+ applicants for Director, Staff and Senior Engineering roles for Machine Learning and Data engineering. - Developed a zero-shot learning model that achieved 80%+ precision in identifying seniority and function among 500MM job titles. - Improved the quality of the CRM product by identifying incorrect merged records from 100 MM data points.

Machine Learning Lead

- Created the machine learning team, led strategic planning of the roadmap and helped hire 8 data science researchers and machine learning engineers working across 3 continents and 4 countries. - Health Tech Startup aiming to simplify healthcare access by providing rapid and accurate disease screening services. - Created a cough detector model using deep learning which can reveal whether an audio sample has cough with at least 90% accuracy that powered a clinically approved covid detector, the core technology of the application. - Led the development of a deep learning pipeline that can classify cough samples into COVID-19 and non-COVID-19