Vaclav Petricek
Head Of Generative AI
Greater Seattle Area United States
Summary
👤
Senior🎓
Top SchoolVaclav Petricek is a seasoned AI and engineering leader with 14+ years building large-scale ML and search systems, currently leading Generative AI efforts at Amazon where he launched the Rufus shopping experience and led pretraining, fine-tuning (IFT/SFT/RLHF/RLAIF/PPO/DPO) and trust-and-safety alignment for large foundation models. He previously ran Global Search Quality, solving multilingual semantic matching, extreme multi-class classification, and graph-scale problems across Seattle, Bangalore and Palo Alto. A hands-on builder throughout his career, Vaclav contributed to core Vowpal Wabbit algorithms and optimized its deployment on YARN/MR2, reflecting deep expertise in both ML algorithms and MLOps. He founded consulting engagements and led machine learning at eHarmony and Live Nation, shipping real-time recommenders and personalization at scale. Equally comfortable with research and production, he holds advanced degrees from Charles University and has mentored startups through Techstars Sustainability Paris. Notably, his teams deliver unified RAG systems with federated dense retrieval and planning—tying cutting-edge research directly to product impact.
14 years of coding experience
17 years of employment as a software developer
Entrepreneurship, Entrepreneurship at London Business SchoolPhD Computer Science, PhD Computer Science at Charles University
Czech, German, English, French, Russian
Stackoverflow
11reputation
451reached
1answer
1question
Github Skills (16)
machine-learning10
c-language10
cprogramming-language10
elearning10
devops9
parallel-computing9
shell8
script8
sh8
scripting8
bandit7
master-slave6
hadoop6
searching6
active-learning5
Programming languages (2)
Github contributions (5)
VowpalWabbit/vowpal_wabbit
Mar 2012 - Jun 2014
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Role in this project:
Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:54 commits in 2 years 3 months
Contributions summary:Vaclav contributed to the core functionality of the Vowpal Wabbit machine learning system by implementing and improving the BFGS optimization algorithm, including its integration with the regularization features. They also worked on the system's build and deployment by modifying the shell scripts for running parallel learning on YARN/MR2. The commits demonstrate a focus on enhancing the core machine learning algorithms and supporting the system's deployment infrastructure.
hashingtechniquescpppythonactive-learning
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