Mikko Juola
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMikko Juola is a seasoned software engineer with 15 years of experience building reliable, real-time systems across adtech, payments, and large-scale messaging platforms. Based in San Francisco, he has worked on high-impact infrastructure at NextRoll, Pinterest, and Meta (WhatsApp), focusing on data pipelines, attribution, and account-management systems serving hundreds of millions of users. He blends functional-programming fluency (Haskell) with practical systems work—contributing Haskell bindings for the efficient TrailDB event store—and enjoys digging into VM internals, memory visualization and on-call reliability. Mikko is also fascinated by algorithmic prediction and automated trading, applying the same engineering rigor to researching betting systems for horse racing and e-sports. He mentors and leads technical teams, aiming to deliver outcomes that scale for customers while growing the people around him.
15 years of coding experience
7 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Aalto UniversityComputer Science, Computer Science at Korea Advanced Institute of Science and Technology
English, Finnish, Swedish, Japanese
Github Skills (12)
c1710
c1110
ffi10
haskell10
ff10
databases9
database9
data-structure9
time-series9
data-structures9
big-data9
cabal8
Programming languages (9)
Github contributions (5)
traildb/traildb
Aug 2015 - Nov 2019
TrailDB is an efficient tool for storing and querying series of events
Role in this project:
Back-end Developer
Back-end DeveloperContributions:75 commits, 5 PRs, 9 pushes in 4 years 3 months
Contributions summary:Mikko implemented Haskell bindings for the TrailDB library, focusing on core functionalities like constructing new TrailDBs, opening existing ones, and accessing features. They added functions for handling cookies, fields, and values within the library, along with utilities for traversing and manipulating data within the TrailDB structure. Furthermore, the user incorporated exception handling and added support for generating and managing multiple TrailDBs through directory-based operations.
bigtabledata-analyticseventsqueryingstoring
Noeda/mj-lstm
Mar 2020 - Mar 2025
Contributions:68 pushes, 1 branch in 5 years 1 month
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