Senior Machine Learning Engineer - Esports (m/f/x)

Wroclaw, Dolnośląskie, Poland Remote April 15, 2026 Full Time
  • Are you excited about building ML systems that make predictions in real-time?

  • Are you driven by building things end-to-end, from research to live systems?

If the answers to the above questions are yes, then this role could be ideal for you!

About the role

We are building real-time prediction systems for competitive esports (CS2, Dota2, League of Legends). Our models power live betting markets, producing continuously updated win probabilities, handicap lines, over/under totals, and specialty markets during matches.

We are looking for a Senior ML Engineer to own the full lifecycle of our prediction models: from research notebooks to production-grade ML pipelines, deployed at scale in a real-time microservices architecture.

Requirements

What you will do 

  • Convert existing model training code into reproducible, automated pipelines (experiment tracking, model versioning, automated retraining), following ML best practices

  • Work on algorithms and probabilistic market-derivation logic that powers our live predictions

  • Define evaluation metrics, build backtesting frameworks, and monitor model performance in production

  • Serve models via a Python microservices stack

  • Work with the product team to define new betting markets and the statistical models that support them

Your skills will include

  • 5+ years of professional experience in ML engineering or applied data science

  • Experience developing production-grade ML pipelines and are familiar with workflow orchestration, experiment tracking and CI/CD for ML

  • Knowledge of object-oriented programming, using vector operations for optimized performance, and a deep understanding of memory management

  • A strong grasp of probability and statistics

Nice to have

  • Experience with real-time / streaming ML, models that update or serve live predictions

  • Familiarity with betting / trading / quantitative finance, understanding of odds, overround, market-making, or any domain where calibrated probabilities matter

  • Experience building MLOps infrastructure

  • Knowledge of esports or sports analytics

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How well do you match this role?

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