Jayant Jain
Member Of Technical Staff at Augment Code
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJayant Jain is a backend and ML-focused software engineer with 13 years of experience building scalable systems and high-performance infrastructure for large-data workloads. He blends practical production engineering—most recently as a Senior Software Engineer at Mixpanel and now at Augment Code—with research-grade NLP and embedding work, having been a core contributor to the widely used Gensim project and an implementer of Poincaré embeddings. His contributions span from deploying XGBoost models and running A/B tests at Uber to IR-driven near-duplicate detection and search systems at Housing.com, showing a knack for turning models into measurable product impact. An active open-source practitioner and early CodeCombat contributor, he also built tooling to analyze news topics and trends, reflecting a persistent interest in applied language understanding. Based in San Francisco, he pairs an MS in Computer Science from Georgia Tech with hands-on curiosity fostered at the Recurse Center, often tackling the intersection of systems engineering and ML.
13 years of coding experience
8 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Georgia Institute of TechnologyIndian Institute of Technology RoorkeeSanskriti School, New Delhi
English, Hindi
Github Skills (20)
editors10
gensim10
javascript10
coffeescript10
word2vec10
python10
editor10
natural-language-processing10
scene-editor10
nlp10
data-science9
ui-design9
sass9
front-end-development9
topic-modeling9
Programming languages (7)
Github contributions (5)
piskvorky/gensim
Jul 2016 - Mar 2018
Topic Modelling for Humans
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:62 commits, 16 PRs, 106 pushes in 1 year 7 months
Contributions summary:Jayant primarily focused on enhancing the functionality and accuracy of the word2vec model within the gensim library. They implemented a case-insensitive option for the word2vec accuracy calculation and fixed related bugs. Additionally, the user contributed to the development of an ipython notebook to compare fastText and word2vec, incorporating improvements, and adding a comparison with the text9 corpus. They also worked on implementing the poincare model.
pythonword-similarityword-embeddingsdata-miningfor-humans
codecombat/codecombat
Mar 2014 - Aug 2014
Game for learning how to code.
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:82 commits in 5 months
Contributions summary:Jayant contributed to the CodeCombat level editor by implementing new features and making improvements to the user interface. Their work included bug fixes for the editor, updates to the thang tab, and the implementation of smoother panning controls for the map. They also added a search bar for adding thangs and a terrain randomisation feature.
game
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