Artur Soler
Software Consultant at Self-Employed
Barcelona, Catalonia, Spain
Summary
👤
Senior🎓
Top SchoolArtur Soler is a Barcelona-based software consultant with 12 years of experience architecting, developing and maintaining backends for web and mobile applications. He blends hands-on engineering with entrepreneurial experience as the founder of Insightware, where he built a next-generation A/B testing product focused on improving conversion over time. His background includes acceleration of financial applications at Maxeler and early product work in rapid prototyping tools, giving him a mix of performance-oriented and product-focused engineering. An active contributor to open-source ML infrastructure, he enhanced RecommendationIO’s recommendation templates to support multi-category queries and item weighting—practical improvements that boost recommendation flexibility and relevance. Known for tackling tricky problems with pragmatic technical design, he pairs deep backend expertise with a strong product sensibility.
12 years of coding experience
4 years of employment as a software developer
UPC Universitat Politècnica de Catalunya
English, Catalan, Spanish, French
Stackoverflow
3,014reputation
279kreached
26answers
16questions
django
top-5%
unit-testing
top-5%
Github Skills (11)
big-data10
machine-learning10
recommendation-system10
predictionio10
scala10
django9
spark9
unit-testing9
callback6
language-design6
web-application6
Programming languages (5)
Github contributions (5)
apache/predictionio
Mar 2015 - Mar 2015
PredictionIO, a machine learning server for developers and ML engineers.
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 2 PRs, 2 comments in 14 days
Contributions summary:Artur contributed to the development of a recommendation engine, specifically focusing on modifying and extending an existing recommendation template. Their work involved adding features such as filtering results by category and adapting the model to accept multiple categories within a query. The changes also included integrating the use of item weights, which involved modifying the scoring and prediction logic of the recommendation model. These modifications indicate a focus on enhancing the flexibility and functionality of the recommendation system within the project.
machine-learningpredictionioscalabig-data
ArturSoler/scala-js-website
Oct 2015 - Nov 2017
Contributions:2 pushes in 2 years 1 month
scalajsscalascala-jsjs-org
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