Artem Komarov
Hi, I’m Artem Komarov. I am a Software Engineer with a strong background in building production-grade systems across backend, cloud infrastructure, and machine learning.
About
Hi, I’m Artem Komarov. I am a Software Engineer with a strong background in building production-grade systems across backend, cloud infrastructure, and machine learning. I enjoy working across the stack with a focus on performance, scalability, and writing clean code that solves real-world problems. I have experience with multiple programming languages such as Go, Python, and C++, and I am passionate about applying AI technologies effectively.
Currently based in Hamburg, Germany, I’ve worked on some ambitious projects including cloud platform development, AI model deployment automation, and software modernization for large enterprises. I constantly enjoy learning new skills and improving my craft in the fast-moving tech industry.
- 3 years' experience
- Joined June 2025
Skills· 15
Languages
- EnglishAdvanced
- UkrainianFluent
- RussianFluent
- GermanBeginner
Industry experience
- Software & Internet
- Computers & Electronics
- Retail
- Telecommunications
Work experience· 6 roles
Developed a proprietary cloud platform, implementing Go-based microservices as core components of the system’s backend architecture. Automated the deployment of AI models to ease A/B testing and speed up model deployment. Contributed to rebuilding Lidl's legacy warehouse system into a scalable microservices-based platform.
Built, optimized, and deployed relevance ranking models used in product search within large-scale eCommerce systems. Increased the search success rate by 1%, contributing significantly to the company’s annual revenue of €500 million. Automated AI model deployment to facilitate easier A/B testing and faster rollout of new models. Developed a proprietary cloud platform using Go-based microservices as core backend components.
Developed and optimized a C++ AI library for on-device training targeted at resource-constrained environments. Implemented sparse weights and training algorithms reducing model size by 50%. Optimized large language model layers, increasing processing speed by 20% while maintaining output quality.
Education
Certifications and awards· 8
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