Ayush Goel
Research Scientist at Meta
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolAyush Goel is a data scientist and full-stack engineer from UC Berkeley with eight years of hands-on experience building machine learning models and production web systems for startups and campus projects. He combines a rigorous Computer Science and Economics background (3.98 GPA) with strong mathematical instincts, teaching CS 70 and CS 189 discussion sections and mentoring students through complex probabilistic and ML concepts. At Goliath Data he scaled data ingestion and deduplication pipelines, cutting query latency from minutes to milliseconds and enabling nationwide lead coverage, and at seer. he shipped a real-time AI-driven assignment authenticity feature. His open-source contributions include implementing CART decision and regression trees in a Go ML library, showing both applied ML and low-level algorithmic skills. Comfortable spanning model development, backend architecture, and product-facing features, he brings a practical blend of research-level rigor and startup delivery velocity.
8 years of coding experience
4 years of employment as a software developer
Don Bosco High School - IndiaDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of MichiganBachelor of Technology (B.Tech.) Computer Science, Bachelor of Technology (B.Tech.) Computer Science at Indraprastha Institute of Information Technology, Delhi
English, Hindi, Sanskrit
Stackoverflow
375reputation
10kreached
22answers
0questions
Github Skills (19)
classification10
machine-learning10
regression10
go10
decision-tree10
data-structure9
algorithm9
algorithms9
data-structures9
neural-network6
keras6
tensorflow-lite6
deep-learning6
tensorflow6
sum6
Programming languages (5)
Github contributions (5)
sjwhitworth/golearn
Jul 2020 - Nov 2020
Machine Learning for Go
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 42 commits, 3 PRs in 3 months
Contributions summary:Ayush implemented a Decision Tree Classifier, including the CART (Classification and Regression Tree) implementation using Gini Impurity or Entropy as user selected parameters. They added integration for Fixed Data Grids in Predict and Evaluate functions, demonstrating a focus on model training and prediction. Furthermore, the user added regression trees functionality to the project, thereby expanding its machine learning capabilities and contributing new model types. The user also added comments and documentation for the new regressor.
golangmachine-learningdata-science
Yushgoel/golearn
Jul 2020 - Nov 2020
Machine Learning for Go
Contributions:16 PRs, 40 pushes, 6 branches in 3 months
golangmachine-learningdata-science
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