Sebastian Hätälä
Software Engineer, Machine Learning at Meta
Bonn, North Rhine-Westphalia, Germany
Summary
🤩
Rockstar🎓
Top SchoolSebastian Hätälä is a software engineer specializing in machine learning with a decade of experience building production ML services and leading teams across Europe. Currently at Meta, he brings hands-on expertise in PyTorch-based modeling and FastAPI-driven services from his prior role scaling ML features at LeanIX. His background spans consulting and management at zeb consulting and a brief founding stint, giving him a pragmatic blend of product, technical leadership, and client-facing delivery. An active backend contributor, he enhanced an open-source LinkedIn scraping library to extract nuanced profile attributes like interests and accomplishments, demonstrating attention to data modeling and scraping robustness. Based in Bonn, Germany, he couples formal studies in information systems and IT management with a track record of moving models from research prototypes into reliable services. Colleagues would describe him as a technically curious engineer who thrives at the intersection of systems, data and product.
10 years of coding experience
5 years of employment as a software developer
Master of Science (M.Sc.), Management of Information Technology, Master of Science (M.Sc.), Management of Information Technology at University of NottinghamBachelor of Science (B.Sc.), Wirtschaftsinformatik, Bachelor of Science (B.Sc.), Wirtschaftsinformatik at Westfälische Wilhelms-Universität Münster
German, English, Finnish, Czech, French
Stackoverflow
1,015reputation
123kreached
20answers
21questions
Github Skills (22)
selenium10
webscraper10
python10
scrape10
scraper10
selenium-ide10
webscraping10
scrapy10
chrome10
data-scraping10
screen-scraping10
lib9
html9
firefox8
css8
Programming languages (8)
Github contributions (5)
joeyism/linkedin_scraper
May 2020 - May 2020
A library that scrapes Linkedin for user data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 commits, 1 PR in 4 days
Contributions summary:Sebastian primarily contributed to the `linkedin_scraper` library by adding functionality to scrape user interests and accomplishments. This involved modifying the `Person` and `objects` classes in the `linkedin_scraper` package to include attributes for interest and accomplishment data, along with implementing the scraping logic to extract this data from LinkedIn profiles. They also fixed issues in finding person name, refactoring class variables and updating documentation.
firefoxdriverlinkedin-scraperchromelinkedin
hatala91/multipy
Dec 2022 - Dec 2022
torch::deploy (multipy for non-torch uses) is a system that lets you get around the GIL problem by running multiple Python interpreters in a single C++ process.
Contributions:2 PRs, 80 pushes, 4 branches in 11 days
pythongiltorchpython3problem
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