Jakub Piasecki
Summary
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RockstarJakub Piasecki is a Senior Staff Software Engineer with 15+ years building backend-first platforms and applications for enterprise, startup and institutional clients across the US, UK and Europe. He combines hands-on implementation (Java/Kotlin/Groovy, Ruby, Kafka, Flink) with end-to-end ownership from requirements and architecture to deployment and maintenance, including security and compliance for legal and financial domains. Jakub has led engineering practices and hiring, introduced cross-project tech strategy, and delivered diverse systems—from real-time RFID tracking and logistics microservices to mobile banking and solar billing platforms. He is an active contributor to high-performance open-source projects (e.g., adding MKLDNN/BF16 kernels to PaddlePaddle), reflecting a focus on performance optimization for compute-intensive workloads. Based in Warsaw, he pairs deep systems and data-streaming expertise with a knack for translating domain-specific needs (bioinformatics visualisations, carbon-footprint analytics) into production-ready solutions.
6 years of coding experience
Github Skills (7)
web-framework10
c-language10
cprogramming-language10
performance-optimization10
python10
machine-learning9
deep-learning9
Programming languages (3)
Github contributions (5)
PaddlePaddle/Paddle
Dec 2020 - Jan 2023
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Role in this project:
Back-end Developer
Back-end DeveloperContributions:309 reviews, 98 commits, 137 PRs in 2 years 1 month
Contributions summary:Jakub's contributions primarily involve modifying the core framework code within the PaddlePaddle repository. The user's commits introduce and integrate MKLDNN kernels for various operations. They have added, and in some cases refactored, kernels for operations like conv2d, matmul_v2, expand_v2, slice, and activation functions, demonstrating a focus on performance optimization and integration of external libraries. Their work includes significant changes to the core codebase involving file modifications and the introduction of BF16 support in these operations.
pytorchpythonparalleldeep-learningpaddlepaddle
jakpiase/Paddle
Nov 2020 - Feb 2023
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Contributions:651 pushes, 134 branches in 2 years 3 months
pytorchparalleldeep-learningreinforcement-learningindustrial
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