Jay Chakalasiya
Software Engineer - Machine Learning at Google
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolJay Chakalasiya is a machine learning engineer based in Mountain View with nine years of experience building production ML systems and data-driven products across startups, academia, and Google. He blends deep learning (vision and NLP), search/ranking, and distributed data engineering skills with hands-on software development in Python, C++, PyTorch/TensorFlow and Spark. His background includes leading end-to-end projects—from architecting OCR+LSTM systems that digitized 10k+ books for accessibility to shrinking data pipelines from 24 hours to 2 minutes—demonstrating a focus on measurable impact. He pairs technical execution with product and user research skills developed through capstone and startup roles, designing dashboards and prototypes used by clinicians and educators. Comfortable at the intersection of tech, design, and business, he brings both research rigor (MS degrees from Tsinghua and University of Washington) and practical deployment experience at scale. An engineer who describes himself simply as "AI, ML and Fun," he favors pragmatic solutions that improve accessibility and operational efficiency.
9 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Technology Innovation, 3.95/4.0, Master of Science - MS, Technology Innovation, 3.95/4.0 at University of WashingtonBachelor of Technology - BTech, Computer Science, 8.6/10, Bachelor of Technology - BTech, Computer Science, 8.6/10 at Nirma UniversitySpecialization in Information Security, Computer Science, 8.6/10, Specialization in Information Security, Computer Science, 8.6/10 at Nirma University, Ahmedabad, Gujarat, IndiaMaster of Science and Engineering, Data Science, 4/4, Master of Science and Engineering, Data Science, 4/4 at Tsinghua University
English, Hindi, Gujarati
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (30)
cv-template9
weighted9
jekyll9
resume9
efficientnet8
jekyll-theme8
mobilenet8
fusion8
predict7
ensemble-learning7
re-identification7
computer-vision7
object-detection6
datasets6
feature-selection5
Programming languages (4)
Github contributions (5)
jay-chakalasiya/jay-chakalasiya.github.io
Jun 2017 - Nov 2020
http://jay-chakalasiya.github.io
Contributions:117 pushes, 2 branches in 3 years 5 months
jay
jay-chakalasiya/Global-Wheat-Detction-Kaggle-2020
May 2020 - Jul 2020
For the Kaggle Competition on object detection with same name. 1) models used are DETR, EfficientDet, YOLOv5, RetinaNet, FasterRCNN. 2) Ensemble inference using Weighted Box Fusion 3) Pseudo Learning to deal with smaller labeled datasets. 4) Mixup as an augmentation technique
Contributions:55 commits, 2 PRs, 36 pushes in 1 month
kagglefasterrcnndealretinanetensemble
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