Summary
Atharva Kulkarni is a Senior Consultant in Machine Learning with seven years of hands-on experience building and productionizing ML systems for startups and Fortune-scale companies from San Diego. He has driven measurable business impact—doubling forecasting accuracy on 50,000 time series, cutting inference latency from 3s to 150ms, and accelerating support resolution by 40% through RAG systems integrating multiple enterprise sources. Comfortable across the ML lifecycle, he has scaled training with Ray, refactored pipelines handling 100M emails/day, and resolved complex dependency conflicts in large-scale AWS/SageMaker environments. Atharva pairs research curiosity (work on latent diffusion models and microbiome analysis) with product-focused engineering, regularly collaborating with stakeholders to turn prototypes into deployed services. He also brings leadership experience running UCSD’s Data Science Student Society and mentoring teams of 40+, blending technical depth with people and project management. Notably, his background shows a pattern of replacing external dependencies with in-house models and systems that improve performance and cut costs.
7 years of coding experience
3 years of employment as a software developer
University of California, San Diego
Marathi, Hindi, English, Spanish