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.
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
