Summary
Fenil Doshi is a Lead Member of Technical Staff at Slack with eight years of full-stack and machine learning engineering experience, known for bridging research-grade ML with production data infrastructure. He holds a 4.0 MS in Computer Science from UMass Amherst and has shipped impact-driven systems across Slack, Unity, and startup robotics/vision teams—most recently driving Apache Iceberg adoption and CDC-based ingestion architecture. Fenil’s background spans Java, Go, Python, C/C++, and modern ML stacks (PyTorch, TensorFlow, OpenCV) and includes measurable wins like lowering Unity’s ad-pipeline costs and boosting referential-game accuracy in Meta AI research. Equally at home mentoring students—he taught a first-year UMass seminar—and contributing to open-source lineage tooling, he combines pragmatic system design with an appetite for experimental ML and developer-facing data platforms.
8 years of coding experience
6 years of employment as a software developer
11th- 12th Science, 11th- 12th Science at Pace Science Junior College
Master's degree Computer Science, Master's degree Computer Science at University of Massachusetts Amherst
10th, 10th at Friends High School
Bachelor of Engineering - BE Computer Science, Bachelor of Engineering - BE Computer Science at Dwarkadas J. Sanghvi College of Engineering
English, Gujarati, Hindi, Marathi