Laurynas Tamulevicius
Staff Machine Learning Engineer at Google
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolLaurynas Tamulevicius is a Senior Machine Learning Engineer with a decade of experience building scalable ML and cloud systems, currently working on Google Cloud Vertex AI Search in Zurich. He combines a strong research background in quantum information (MSc in Computer Science and Physics, exchange at UIUC) with hands-on production expertise across YouTube search and ads, site reliability, and full-stack web platforms. Laurynas has authored multiple generative-AI invention disclosures and helped operationalize large services, mentoring engineers and improving relevance and deployment pipelines. An active contributor to quantumlib/qsim, he’s improved simulator memory management, multi-SIMD support, and CI/CD for macOS wheels—showing deep systems-level optimization skills beyond typical ML work. Colleagues know him for bridging low-level performance tuning and high-level product impact while keeping a curious, interdisciplinary approach to problem solving.
10 years of coding experience
9 years of employment as a software developer
Exchange Student, Computer Science and Physics, Exchange Student, Computer Science and Physics at University of Illinois Urbana-ChampaignMaster’s Degree, Computer Science and Physics, Master’s Degree, Computer Science and Physics at University of Glasgow
English, Lithuanian, German, Russian
Stackoverflow
1,569reputation
252kreached
28answers
22questions
Github Skills (20)
circuit10
simulation10
algorithms10
c-language10
simulator10
simulations10
quantum-computing10
cpp10
cprogramming-language10
cicd9
numpy9
python8
cmake8
flask6
django-templates6
Programming languages (4)
Github contributions (5)
quantumlib/qsim
May 2021 - Aug 2021
Fast C++ and Python library for state-vector simulation of quantum circuits.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:3 reviews, 25 commits, 12 PRs in 3 months
Contributions summary:Laurynas primarily focused on improving the simulator's memory management and adding support for multi-SIMD instructions, indicating a focus on performance optimization. They fixed memory deallocation issues in the C library interface. Furthermore, the user set up and configured CI/CD build processes, particularly for MacOS wheels. These contributions suggest a strong understanding of the codebase's underlying architecture and build processes.
cpppythonsimulationquantum-computingquantum-simulator
KwiatLab/quantum-key-distribution
Apr 2016 - Nov 2016
Contributions:99 commits, 97 pushes, 2 branches in 6 months
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