Javier De La Rúa Martínez
Research Engineer at Hopsworks
Sweden
Summary
🤩
Rockstar🎓
Top SchoolJavier De La Rúa Martínez is a research engineer and PhD candidate at KTH with 11 years of experience building scalable machine learning systems and data platforms. He focuses on Feature Stores and production-grade data management for ML, contributing backend work to the well-known Hopsworks platform to improve secure API file access. Javier blends research and hands-on engineering—having implemented ML model monitoring architectures with Spark, Kafka, and Kubernetes—and brings prior experience integrating Arrow and Parquet into HTAP engines. Based in Sweden, he combines academic rigor in scalable ML systems with practical startup experience delivering backend services and monitoring tooling. An always-learning, enthusiastic collaborator, he also pursues applications of AI to medical and neuroscience domains.
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Scalable Machine Learning Systems, Doctor of Philosophy - PhD, Scalable Machine Learning Systems at KTH Royal Institute of TechnologyMaster's degree in Data Science (EIT Digital), Artificial Intelligence, Master's degree in Data Science (EIT Digital), Artificial Intelligence at Universidad Politécnica de Madrid
english - c1 cambridge level, Spanish, german - a1 level
Github Skills (12)
javas10
authentication10
user-authentication10
api10
apidoc10
java10
api-design9
restful-api9
rest-api9
api-rest9
ruby7
junit6
Programming languages (10)
Github contributions (5)
logicalclocks/hopsworks
Dec 2020 - Dec 2022
Hopsworks - Data-Intensive AI platform with a Feature Store
Role in this project:
Back-end Developer
Back-end DeveloperContributions:24 reviews, 40 commits, 56 PRs in 2 years
Contributions summary:Javier contributed to the development of the Hopsworks API, specifically focusing on adding functionality to download files using API keys. This involved modifying the `DownloadService.java` file to include new API endpoints and authentication checks. The changes also included updates to related test files and helper functions in Ruby. Overall, the user's work centered on enhancing the API's features and ensuring secure access to data files.
gcppythonserverlessai-platformhopsworks
logicalclocks/kserve
Dec 2021 - Mar 2025
Serverless Inferencing on Kubernetes
Contributions:6 reviews, 54 PRs, 28 pushes in 3 years 3 months
serverlessmachine-learningmlopskubernetestensorflow
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