Viljams Volosovskis
Lead Software Engineer at Latvijas Valsts radio un televīzijas centrs
Riga, Vidzeme, Latvia
Summary
🤩
Rockstar🎓
Top SchoolViljams Volosovskis is a Lead Software Engineer based in Riga with 14 years of experience building scalable, automated systems across cloud, mobile, and embedded domains. He blends deep infrastructure expertise—Linux, Kubernetes, Docker, CI/CD and AWS—with hands-on development in Go, Java, TypeScript and mobile native integrations, having led projects from NFC/LoRaWAN sensor apps to large-scale game and MMO server platforms. A container and automation advocate who champions reproducible deployments, he has also contributed machine learning model-saving and context classification improvements to the open-source SerpentAI project and enhanced protobuf code generation in ts-proto. Known for turning complex, production-scale requirements into maintainable pipelines and admin tooling, he combines a pragmatic engineering mindset with an unusual background in large community-run game servers that honed his operational and scaling instincts.
13 years of coding experience
18 years of employment as a software developer
Basic Education, Basic Education at Riga French LyceumBTEC Level 5 Computing, BTEC Level 5 Computing at University of PortsmouthBTEC Level 3 IT and Business, BTEC Level 3 IT and Business at Crawley College
Latvian, English, French
Stackoverflow
722reputation
46kreached
29answers
7questions
Github Skills (24)
python10
machine-learning10
typescript10
keras10
code-generation10
trainings10
typescript-types10
typescripts10
protobuffer10
modeling10
protobuf10
faster-rcnn9
mask-rcnn9
computer-vision9
scikit-learn7
Programming languages (23)
Github contributions (5)
stephenh/ts-proto
Nov 2020 - May 2022
An idiomatic protobuf generator for TypeScript
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:6 reviews, 13 commits, 5 PRs in 1 year 6 months
Contributions summary:Viljams focused on adding support for meta-typings, fixing linter errors, and refactoring code related to protobuf generation. They also switched to a FileDescriptorProto approach for meta generation and implemented proto serialization for meta generation. Further contributions involved adding support for unknown fields and enabling prototype for defaults, indicating a focus on enhancing the project's core functionality and code generation capabilities.
idiomaticcode-generationnestjsprotobufgrpc
SerpentAI/SerpentAI
Sep 2017 - Oct 2017
Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
Role in this project:ML Engineer
ML EngineerContributions:13 commits, 6 PRs, 2 comments in 9 days
Contributions summary:Viljams contributed to the machine learning aspect of the project by adding autosave functionality for training context classifiers and modifying the training process. They worked on the context classification system, specifically the CNNInceptionV3 and SVM classifiers, integrating model saving and validation steps. Additional modifications include changes to the sprite locator for localized region identification and adjustments to boolean handling in the training execution.
gameagentreinforcement-learningbotsais
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