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Krzysztof Staroń — Hacklab

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KS

Krzysztof Staroń

@krzysztofstaron

Freelance ML and full-stack engineer building AI systems for businesses. Projects span neural networks, AI agents and voice-model evaluation.

PolandJoined July 2026

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Last recorded activity: August 5, 2026.

1,939,413,101 tokens across 10 active days this year. Shades reflect this user's activity, with stronger shades for higher daily totals. Session tokens count on their last active day in UTC. Use arrow keys to explore days, or Home and End to jump to the first and last day.

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CV

Accomplishments

handwritingPython repository for a regressive model for realistic handwriting, created June 2026, with 5 stars. Listed as the repository owner on the member's GitHub account.(opens in a new tab)
graph-llmTypeScript repository described as an alternative UX for LLMs and a universal playground for new paradigms in AI, created December 2025, with 2 stars. Listed as the repository owner.(opens in a new tab)
custom-llmPython repository for a tiny language model trained on a personal laptop (2025). Listed as the repository owner.(opens in a new tab)
PromptCoT-implementationPython repository implementing the PromptCoT research paper (2025), with 1 star. Listed as the repository owner.(opens in a new tab)
Filesystem written in RustThe member's website states a filesystem was written in Rust; the public filesystem repository is Rust, created March 2026, and has no repository description.(opens in a new tab)
AutoSniperTypeScript repository for a car listing AI ranking system for Poland (2025). Listed as the repository owner.(opens in a new tab)
companionsTypeScript repository for a Grok-inspired 3D AI companion (2025), with 1 star. Listed as the repository owner.(opens in a new tab)

Experience

Freelance ML Engineer
Aug 2025 – Present
Self-employed · 1 yr 4 mos
Delivers end-to-end AI-system implementations for businesses.
ML Engineer
Aug 2026 – Aug 2026
Dialo · Warsaw, Poland · 1 mo
Worked on voice AI agents whose profile-reported traffic was 1.2 million voice calls per week. Built a pipeline collecting failures to support faster diagnosis and quality improvements, a semi-automated system to acquire/prepare ASR-evaluation data, and a dedicated dataset to benchmark telephone voice agents.