Hi there, I’m Jakub

I am a Machine Learning Engineer based in London. With over six years of prior experience directing an IT operations team, I bring a unique dual perspective to artificial intelligence: I understand both the rigorous engineering required to build predictive models and the practical business constraints required to deploy them effectively.

My core objective is to translate complex data into actionable, scalable solutions that drive measurable business value, optimize operational workflows, and support strategic decision-making.

Technical Expertise & Engineering

My technical workflow is firmly rooted in modern, production-grade Python development and comprehensive machine learning frameworks. I focus on building intelligent systems that are robust, maintainable, and strictly version-controlled.

• Machine Learning & Deep Learning: End-to-end pipeline development using Scikit-Learn, Keras, and TensorFlow. Expertise encompasses robust data preprocessing, feature engineering, classification and regression modeling, and constructing deep neural networks.
• Software Development: Advanced Python programming focusing on clean architecture, efficient data structures, and maintainable codebase design.
• Version Control & CI/CD: Rigorous utilization of Git for source control, coupled with continuous integration workflows (e.g., GitHub Actions) to automate testing and ensure code reliability across collaborative environments.
• Deployment Infrastructure: Practical knowledge of system administration, containerization, and networking, ensuring models are designed for the physical and networked environments they will inhabit.

Leadership & Strategic Problem-Solving

Prior to specializing in AI, I spent six years leading an IT team at a London-based limited company. This tenure instilled a highly pragmatic, outcome-focused approach to engineering:

• Systems-Level Troubleshooting: A proven track record of diagnosing complex technical failures, performing root-cause analysis, and implementing permanent, scalable fixes rather than temporary patches.
• Business Alignment: Experience bridging the communication gap between technical teams and stakeholders, ensuring engineering initiatives directly support overarching business goals and deliver high ROI.
• Risk & Resource Management: Evaluating architectural trade-offs, managing project lifecycles, and deploying reliable infrastructure that minimizes operational friction and downtime.

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Available for professional inquiries and collaboration via the contact links in the sidebar.