Shrikar Archak
Senior Staff Machine Learning Engineer at Instacart
California, United States
Summary
🤩
Rockstar🎓
Top SchoolShrikar Archak is a Senior Staff Machine Learning Engineer based in California with 14 years of experience building distributed systems, real-time analytics, and large-scale data platforms. He blends deep systems expertise—filesystems, deduplication, indexing and schema design—with production ML work, contributing feature store and S3/Redis integrations to Instacart’s notable lore repository to make ML more maintainable for engineers and researchers. At Instacart he has progressed from hacker to senior staff, driving feature engineering, model deployment and realtime pipelines while earlier roles at Viralheat, Yahoo and EMC sharpened his Storm-based streaming and storage skills. He also ships consumer-grade iOS apps in his spare time, reflecting a pragmatic full-stack mindset that moves ideas from research to user-facing products.
14 years of coding experience
5 years of employment as a software developer
Karnatak UniversityBachelor of Science, Computer Science, Bachelor of Science, Computer Science at RV College Of EngineeringMS, Computer Science, MS, Computer Science at Stony Brook University
Github Skills (10)
pandas10
machine-learning10
feature-engineering10
python10
s3-bucket9
amazon-s39
redis9
aws-s39
data-science8
tensorflow3
Programming languages (9)
Github contributions (5)
instacart/lore
Oct 2017 - May 2019
Lore makes machine learning approachable for Software Engineers and maintainable for Machine Learning Researchers
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 24 commits, 10 PRs in 1 year 6 months
Contributions summary:Shrikar contributed significantly to the `instacart/lore` repository, which focuses on making machine learning approachable. Their contributions included adding feature store functionality and defining core feature classes. The user also implemented and tested various features, including S3 and Redis integrations, and addressed dependencies and configuration for the feature store. They demonstrated a deep understanding of feature engineering and model deployment within the machine learning context of the project.
machine-learningpython
sarchak/self_driving_car
Nov 2016 - Feb 2017
Contributions:54 commits, 29 pushes, 1 branch in 2 months
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