Miklos Szegedi is a software engineering specialist and founder with nine years of formal experience and a two-decade technical pedigree spanning embedded drivers to large-scale distributed systems. He builds tech assets aimed at institutional investment and retirement funds while also running stealth AI ventures and open-source reference projects for AI code generation. A pragmatic full-stack engineer, he has shipped storage and compute features at Amazon Redshift, contributed backend fixes to Apache Hadoop/YARN, and led autoscaling work in Go at Cloudera. Currently focused on AI/LLM training at SpaceX and co-founding an AI-native transaction verification startup, he blends low-level systems knowledge (chip testing, codecs, firmware) with cloud, data streaming, and ML stacks. Beyond engineering, he serves as a substitute teacher and holds an MBA, signaling an uncommon mix of technical depth, operational leadership, and community engagement. He publishes under a pen name and funds open-source R&D through contract work, turning contracting proceeds into reusable AI and RAG reference solutions.
9 years of coding experience
24 years of employment as a software developer
German as a Second Language, German as a Second Language at Österreichische Institut
Master of Business Administration - MBA, Business Administration and Management, General & Finance, Master of Business Administration - MBA, Business Administration and Management, General & Finance at Louisiana State University
Ballroom Dancing, Ballroom Dancing at New York Dance Association, Budapest, Hungary
M.Sc., Information Technology - Computer Science, M.Sc., Information Technology - Computer Science at Budapest University of Technology and Economics
High School Diploma, ELTE Radnóti Miklós Gyakorló Általános Iskola és Gyakorló Gimnázium, High School Diploma, ELTE Radnóti Miklós Gyakorló Általános Iskola és Gyakorló Gimnázium at Eötvös Loránd University
Machine Learning, Machine Learning at Stanford Continuing Studies
Certificate, Digital Marketing, Certificate, Digital Marketing at Cornell University
Contributions:47 commits, 14 PRs, 73 comments in 7 months
Contributions summary:Miklos contributed to the Apache Hadoop project by addressing memory limit issues and improving logging in the YARN framework. They modified the `ContainersMonitorImpl` class to provide more detailed error messages when memory limits are exceeded. Furthermore, they improved the `ContainerLogAppender` and `ProcfsBasedProcessTree` components, enhancing logging and process tree functionalities within the YARN ecosystem. They also addressed a bug within the FairScheduler framework.
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