Anavil Tripathi
Senior Machine Learning Engineer at Moloco
Bellevue, Washington, United States
Summary
👤
Senior🎓
Top SchoolAnavil Tripathi is a Senior Machine Learning Engineer with 11 years of experience building production ML systems for ads, ranking, and content integrity across Meta, TikTok, and Moloco. He has shipped 0-to-1 integrity products that detect and enforce against violating content and trained new ranking models that drove revenue uplift for video surfaces. Comfortable across research-to-production lifecycles, he pairs deep ML modeling with rigorous test automation—evidenced by contributions to the pgmpy probabilistic inference library where he strengthened test coverage for Bayesian and Markov inference. Based in Bellevue, WA, he holds an M.S. in Computer Science from Texas A&M and began his career spanning telecom operations to growth-focused internships, giving him a pragmatic systems-and-product mindset. Colleagues know him for turning complex detection problems into reliable, production-grade pipelines.
11 years of coding experience
9 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Texas A&M UniversitySummer Intern Rectangular Microstrip Antenna Design and Fabrication, Summer Intern Rectangular Microstrip Antenna Design and Fabrication at Indian Institute Of Information Technology Allahabad Bachelor of Technology (B.Tech.) Electronics Engineering, Bachelor of Technology (B.Tech.) Electronics Engineering at Indian Institute of Technology (Banaras Hindu University), Varanasi
English, Hindi, French
Github Skills (7)
inference10
python10
numpy10
testing10
structures6
struct6
causal-inference5
Programming languages (2)
Github contributions (5)
pgmpy/pgmpy
Jan 2016 - Mar 2016
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:13 commits, 14 PRs, 55 comments in 1 month
Contributions summary:Anavil's contributions primarily involved adding and modifying tests for the `pgmpy` library. The user implemented new test cases for Markov models within the `exactInference` module. Furthermore, the commits included changes to test files related to inference and read/write functionalities, demonstrating a focus on ensuring the correctness and reliability of the library's probabilistic and causal inference features. The user also addressed documentation and code style issues across tests.
causal-modelspythondagbayesian-inferencecausal
abhinayyar/SE_DSE_ACSS
Oct 2015 - Dec 2015
Contributions:8 PRs, 47 pushes, 8 branches in 1 month
pythonassociationscoringtexasauctioneer
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