AI Engineering Notebook
I experiment with LLMs, machine learning, deep learning, and data science. This is my portfolio, blog, and technical journal of things I learn and build.
GitHub
I work with language models, prompt engineering, and response evaluation.
I build retrieval-based systems and knowledge bases: vector search, hybrid retrieval, sourced answers.
Tool-using agents, planning loops, memory, evaluation, and controlled automation with LLM-based systems.
Classical models, feature selection, validation, and interpretation of results.
Neural networks, CNNs, RNNs, transformers, and representation learning.
Data analysis, visualization, statistics, and dataset exploration.
Image understanding, document parsing, text extraction, layout analysis, and vision-language pipelines.
Diffusion, multimodal generation, and model workflows for visual content understanding and creation.
Solution design, ML pipelines, and experiment prototyping.
The public product site for MobiSkan, built on Joomla with a fully custom template. The only parts of Joomla core actually reused are the CMS content…
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MobiSkan WMS is the server-side counterpart to the MobiSkan Android application. It turns individual CipherLab data collectors into one coordinated wa…
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MobiSkan is an offline-first Android application for warehouse staff carrying CipherLab data collectors (RK25, RK26, RK95): receiving goods, issuing s…
View projectEducative · Employer-Sponsored · 2026
Focused on architecting scalable, production-grade ML systems. Covered end-to-end pipeline design, infrastructure trade-offs, and reliability considerations. Emphasized latency, monitoring, and deployment best practices derived from large-scale industry environments.
Udemy · Independent Study · 2026
Designed multi-agent architectures using LangGraph, CrewAI, and AutoGen. Implemented tool orchestration, task routing, and Docker-based deployments. Delivered complex agent collaboration systems including autonomous trading simulations.
LinkedIn · Employer-Sponsored · 2026
Explored transformer architectures and post-GPT-3 LLM advancements. Analyzed architectural evolution and real-world NLP applications. Strengthened practical understanding of LLM deployment strategies.
Udemy · Independent Study · 2026
Built responsive web applications using semantic HTML5 and modern CSS (Flexbox, Grid). Applied structured layout systems and UI/UX principles. Strengthened frontend debugging and optimization skills.
Udemy · Independent Study · 2025
Implemented distributed MapReduce jobs in Python (MRJob) within the Hadoop ecosystem. Executed large-scale workloads locally and on AWS EMR. Applied NLP and analytical processing to real-world Big Data datasets.
I am open to AI engineering roles, applied machine learning projects, technical collaboration, and focused project discussions.
pawel.labuda@itvix.pl