Summary
Sharath Satish is an Associate Software Engineer at Goldman Sachs with eight years of experience building secure, data-driven web and cloud applications. He holds an MS in Computer and Information Sciences from the University of Utah, where his research spanned federated learning for CNNs, fine-tuning Hugging Face LLMs for watermark detection, reinforcement learning for reward learning, and Bayesian optimization for hyperparameter tuning. At the Eccles Institute he accelerated RNA-seq pipelines (7x decompression on 9TB) and engineered clinical features in Postgres to support Bayesian analyses linking obesity, hyperlipidemia, and cancer—work that fed experimental validation in wet labs. Earlier at Accenture he delivered full-stack solutions and Azure-powered Teams bots, improving user productivity and hardening JWT-based authentication across microservices. He combines applied ML research with practical engineering—equally comfortable optimizing Linux data pipelines, designing APIs, or prototyping ML-driven features. Outside of work he’s an avid landscape photographer and hiker based in Salt Lake City, bringing curiosity and a data-first mindset to scientific and product problems alike.
8 years of coding experience
1 year of employment as a software developer
Bachelor of Engineering - BE, COMPUTER AND INFORMATION SCIENCES AND SUPPORT SERVICES, 3.71, Bachelor of Engineering - BE, COMPUTER AND INFORMATION SCIENCES AND SUPPORT SERVICES, 3.71 at JSS Academy Of Technical Education Karnataka
The University of Utah
Secondary School, Computer Science, 93.4%, Secondary School, Computer Science, 93.4% at Kendriya Vidyalaya Mysore
English, Kannada, Hindi