Sushant Gakhar is a software engineer with 11 years of experience specializing in statistical methods for machine learning and practical neural network solutions. He has applied research-grade ML techniques across industry roles—from building scalable systems at Bloomberg to his current engineering role at Meta—while teaching and extending his academic studies in data science at Indiana University. His hands-on projects include quantized neural networks and binary embeddings for visual search, hierarchical retrieval algorithms for fast matching, and domain-agnostic keyword mining for temporal news analysis. Comfortable bridging research and production, he has demonstrated aptitude for deploying models and engineering efficient search and anomaly-detection pipelines. Known for combining rigorous statistical thinking with pragmatic engineering, he seeks cutting-edge problems where principled methods meet product-scale constraints.
11 years of coding experience
6 years of employment as a software developer
Master of Science - MS Data Science, Master of Science - MS Data Science at Indiana University Bloomington
Bachelor of Technology - BTech Information Technology, Bachelor of Technology - BTech Information Technology at Manipal Institute of Technology
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