Tomasz Ulinski
Machine Learning Engineer at RTB House
Poland
Summary
👤
Senior🎓
Top SchoolTomasz Ulinski is a Machine Learning Engineer with 11 years of experience building scalable, real-time data platforms and recommendation systems across ad tech and big data environments. He has deep hands-on expertise in Java SE, Hadoop ecosystem (MapReduce, HDFS), Storm, Spark and Cassandra, and a track record of designing high-performance data models and reliable streaming pipelines. At RTB House he progressed from Senior Software Engineer to Machine Learning Engineer, applying production-grade ML and data engineering patterns to low-latency ad systems. Earlier roles include building distributed graph processing and storage solutions, and a stint creating massively parallel spatial computation libraries, demonstrating comfort across Java and C++ at the systems level. Based in Poland with a Master’s in Computer Science, he combines rigorous academic foundations with practical experience assembling open-source stacks into efficient, production systems.
11 years of coding experience
10 years of employment as a software developer
Master's Degree Computer Science, Master's Degree Computer Science at University of WarsawHigh School, High School at Gdynia Bilingual High School No 3
Polish, English
Github Skills (65)
multithreading10
client-library10
partitioning10
backpressure10
avro9
kafka-consumer9
parallel9
stream-processing9
kafka9
rest-api8
linter8
schema8
confluent8
json8
json-schema7
Programming languages (4)
Github contributions (5)
RTBHOUSE/kafka-workers
Nov 2018 - Sep 2021
Kafka Workers is a client library which unifies records consuming from Kafka and processing them by user-defined WorkerTasks.
Contributions:4 reviews, 88 commits, 28 PRs in 2 years 10 months
parallel-consumermultithreadingstream-processingrecordskafka-consumer
RTBHOUSE/mimuw-lab
Apr 2022 - Aug 2022
Contributions:5 PRs, 21 pushes, 2 branches in 4 months
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