Senior Staff Engineer

Michal Racko

AIData ScienceSoftware Engineering

I design and deliver production AI, machine learning, and data systems that solve complex business problems. My work spans applied research, optimization, and software architecture, leading engineering teams from early exploration through production deployment.

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01

About

I have over a decade of experience designing and delivering AI, machine learning, and software systems from applied research to production platforms serving enterprise customers. My work spans optimization, predictive modeling, fraud detection, decision intelligence, computer vision, and large-scale data systems across manufacturing, retail, cybersecurity, healthcare, and finance.

My background combines studies in astrophysics and high-energy physics at Imperial College London, research as part of CERN's ATLAS collaboration with hands-on software engineering. I enjoy working at the intersection of research and engineering, translating complex ideas into reliable production systems.

I started my career as a data scientist, building machine learning models and analytical systems. Over time, my focus expanded to software engineering, system architecture, and technical leadership. Today, I lead engineering teams, define technical direction, and guide projects from early exploration to production deployment, working closely with researchers, engineers, and business stakeholders to deliver measurable business outcomes.

10+
Years building ML & AI systems
5
Companies, startup to enterprise
CERN
ATLAS research alumnus
Portrait of Michal Racko

02

Skills

Technical expertise across AI, data science, software, and engineering leadership.

Technical leadership

  • Software Architecture
  • System Design
  • Team Leadership
  • Technical Strategy
  • Mentoring
  • Project Leadership
  • Product Thinking
  • Stakeholder Mediation
  • Agile Delivery

AI & Machine Learning

  • LLMs
  • Machine Learning
  • Deep Learning
  • Bayesian Networks
  • Explainable AI
  • Feature Engineering
  • Forecasting
  • Clustering
  • Computer Vision

Data & Analytics

  • Data Science
  • Statistical Modeling
  • Monte Carlo Simulations
  • Optimization
  • Experiment Design
  • Spark
  • Pandas
  • Numpy

Software Engineering

  • Python
  • TypeScript
  • Agentic Development
  • FastAPI
  • Django
  • Docker
  • Distributed Systems
  • Redis
  • Kafka
  • CI/CD

04

Use Cases

A selection of systems I've designed and shipped — from research prototypes to production platforms.

USSteel Kosice

Batch Annealing Optimization

Led the design and delivery of a production planning engine that automates furnace batch scheduling which is an NP-hard combinatorial optimization problem previously solved manually. Designed a custom optimization approach combining weighted set-packing with a novel Metropolis–Hastings search algorithm to efficiently explore the solution space under operational constraints. The system is deployed in production, reducing planning effort while improving furnace capacity utilization by approximately 5%.

  • Combinatorial optimization
  • Monte Carlo
  • NumPy
  • FastAPI

Online betting & gaming (NDA)

AI Strategy & Discovery

Led a cross-functional technical team in defining an enterprise-wide AI adoption strategy for a major European online betting and gaming company. Evaluated more than 200 AI initiatives across business units, assessing technical feasibility, developing proof-of-concepts, and conducting structured stakeholder analyses to estimate business value and organizational readiness. Produced a prioritized implementation roadmap and decision framework that continues to guide the company's AI investment strategy.

  • AI strategy
  • Consulting
  • Technical feasibility
  • Prototyping

Customer Rewards Platform (NDA)

Legacy Platform Stabilization

Led the engineering team responsible for rescuing and modernizing a business-critical customer rewards platform following a transfer of ownership. Inherited a legacy (vibe-coded) codebase with severe architectural debt, unreliable data pipelines, and significant data integrity issues. Directed a six-month stabilization effort that replaced the backend architecture, restored data consistency, redesigned data ingestion workflows, and established a maintainable engineering foundation.

  • Legacy modernization
  • Production systems
  • Technical leadership

ThreatMark

Banking Fraud Prevention

Developed machine learning models for an enterprise fraud detection platform protecting online banking transactions. Contributed feature engineering for production fraud detection pipelines and designed an explainable Bayesian belief network capable of identifying fraudulent behavior while providing transparent, auditable decision paths.

  • Explainable AI
  • Fraud detection
  • Python
  • ML

Retail Operations (NDA)

AI-Driven Pricing Intelligence Platform

Led the development of an AI-powered pricing intelligence platform for a multi-location retail chain to support data-driven pricing decisions. Directed a cross-functional engineering team in building an LLM-based competitor price intelligence system, a custom clustering-driven pricing model, and a web application integrating product catalogs, purchase prices, competitor pricing, and both B2C and B2B pricing workflows.

  • Agentic AI
  • Pricing models
  • Software engineering
  • ML

Institute of Health Policy

Epidemiological Simulation for COVID-19

Developed a Monte Carlo simulation of COVID-19 transmission in Slovakia to support the validation of national epidemiological models. Built the simulation using municipal demographic data, epidemiological statistics, and aggregated telecommunications mobility data to closely model real-world population dynamics and disease spread. The resulting model provided an independent reference for evaluating the assumptions and predictions of the forecasting models used to inform government policy.

  • Monte Carlo
  • Epidemiology
  • Python

03

Experience

A decade of applied AI and machine learning—from academia to industry, and from hands-on model development to leading teams delivering production systems.

  1. Senior staff engineer - Sudolabs

    Apr 2026 — PresentRemote / Contract

    Promoted to Senior Staff Engineer, leading the technical delivery of multiple concurrent client engagements spanning AI, machine learning, software engineering, and data platforms. Provided architectural leadership, mentored engineering teams, and partnered with customers to shape technical strategy, balancing hands-on engineering with technical leadership across the project portfolio.

    • Engineering leadership
    • Software architecture
    • Technical consulting

  2. Staff engineer - Sudolabs

    Apr 2025 — Apr 2026Remote / Contract

    Promoted to Staff Engineer, taking technical ownership of one to two concurrent client engagements. Led teams delivering generative AI, machine learning, and software solutions, spanning web application development, LLM integration, and technical consulting.

    • Technical leadership
    • Backend engineering
    • Machine Learning

  3. Senior data scientist - Sudolabs

    Sep 2024 — Apr 2025Remote / Contract

    Designed and delivered machine learning solutions for the steel and petrochemical industries, working on projects spanning production optimization, computer vision, and predictive maintenance. Collaborated closely with customers to translate operational challenges into production-ready AI systems.

    • Machine learning
    • Computer vision
    • Python

  4. Cybersecurity researcher - ThreatMark

    Mar 2022 — Sep 2024Remote / Contract

    Developed core machine learning components of an explainable fraud detection platform protecting online banking transactions for enterprise customers. Contributed feature engineering and probabilistic modeling to deliver accurate and auditable fraud detection.

    • Explainable AI
    • Fraud detection
    • Python

  5. Senior ML engineer - LinkThat

    Dec 2020 — Mar 2022Remote / Contract

    Promoted to Senior Machine Learning Engineer, expanding my responsibilities from model development to production systems engineering. Designed, built, and maintained scalable distributed data pipelines for document processing, developed deep learning–based image preprocessing for OCR workflows, and delivered internal web applications supporting document processing and analytics.

    • OCR
    • Deep learning
    • Django
    • NLP

  6. ML engineer - LinkThat

    Sep 2019 — Dec 2020Vienna, AT · Remote

    Designed and implemented machine learning models for an on-premise document processing pipeline, spanning image preprocessing, natural language processing, and document classification.

    • Image preprocessing
    • NLP
    • Classification
    • Python

  7. External advisor - Inštitút Zdravotnej Politiky

    Mar 2020 — May 2020Bratislava, SK

    Built a Monte Carlo simulation of coronavirus spread from municipal data, helping validate the official models used by the government.

    • Monte Carlo
    • Epidemiology modeling
    • Python

  8. Cofounder, Data engineer - Dreamlabs

    Sep 2018 — Nov 2020Bratislava, SK

    Founded an AI startup focused on optimization for e-commerce. Led the design and implementation of the machine learning models and the underlying event-driven platform, building the product from initial concept through production deployment.

    • Kafka
    • ML platform
    • SaaS
    • E-commerce

  9. Data scientist - 01People

    Jun 2017 — Nov 2018Bratislava, SK

    Prepared data visualizations for e-commerce, Monte Carlo simulations of crypto-currency transactions, and ML models for classification and time-series prediction.

    • Data visualization
    • Monte Carlo
    • Time-series
    • Classification

  10. MSci Project - Imperial College London

    Sep 2016 — Jun 2017London, UK

    Applied machine learning techniques to the search for rare particle decays as part of my MSci research at Imperial College London within the LHCb collaboration at CERN.

    • Python
    • Machine learning
    • High energy physics

  11. Bc Project - Imperial College London

    Sep 2015 — Jun 2016London, UK

    Developed numerical simulations of light propagation in curved spacetime as part of my bachelor's thesis in physics. Implemented computational models based on General Relativity to study photon trajectories around Schwarzschild, Reissner–Nordström, and Kerr black holes.

    • Python
    • Numerical methods
    • Astrophysics

05

Education

  1. 2017 — 2019

    Doctoral research in High-energy physics - CERN, ATLAS collaboration

    Geneva, CH

    Conducted research in experimental particle physics as part of CERN's ATLAS collaboration, processing large-scale experimental and simulated datasets and applying statistical inference to measurements of top quark properties.

  2. 2013 — 2017

    MSci Physics (ARCS) - Imperial College London

    London, UK

    Graduated with Dean's List honours (top 10% of the cohort) in Physics, specializing in astrophysics and high-energy physics.

  3. 2005 — 2013

    Secondary education - Jozef Lettrich Grammar School

    Martin, SK

    Won multiple national and international science olympiads in physics, mathematics, and chemistry.

    • Gold - IOAA 2013
    • Silver - IOAA 2012
    • 3rd place - Intel ISEF

06

Let's connect

I'm always open to discussing ambitious AI and software engineering projects, whether that's technical consulting, collaboration, or exchanging ideas. Feel free to reach out on LinkedIn.

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