Machine Learning Engineer

At Oddin.gg, we don’t just follow trends—we forge them. As the fastest-growing tech company in Central Europe (Deloitte Fast 50 Winner, 2024), we are at the forefront of esports analytics and gaming innovation, laying the foundation for a new era in entertainment.

Our technology empowers industry giants like ESPNbet, Betano, Stake, Betway, OpenBet, and Softswiss, setting new standards in the space. Backed by top investors from North America, the UK, and Singapore, we are profitable, ambitious, and rapidly expanding.

You’ll be part of a team with similar backgrounds. Your role will involve analysing data from popular esports titles like Dota2, LoL, and CS2. You’ll identify relationships between these games and develop models that predict various aspects of match outcomes. You’ll apply both statistical and machine learning techniques, carefully selecting appropriate validation metrics to ensure the models’ stability and robustness. Finally, you’ll effectively implement your ideas in test and production environments, receiving firsthand feedback to refine and enhance your models.

🚀 Join us. Together, we will define the future.

Your position on the board

• 🎯Enhance Predictive Accuracy: Design and optimize probabilistic machine learning models for eSports games, driving significant improvements in predictive accuracy and performance.
• 📊Build Robust Data Pipelines: Develop and maintain efficient data pipelines, ensuring seamless data ingestion, transformation, and reliable storage, empowering data-driven insights.
• 🚀Drive MLOps Excellence: Champion MLOps best practices, establishing and refining CI/CD pipelines for automated model training, validation, and rapid deployment.
• 🤝Collaborate on Scalable Solutions: Partner with senior data scientists and engineers to architect and implement robust, scalable deep learning solutions for eSports analysis.
• 🗣️Communicate Complex Insights: Translate intricate model designs and results into clear, actionable insights for colleagues with diverse technical backgrounds, fostering cross-functional understanding.

Our idea of ​​you

• 🚀Drive Production Deployments: Bring a minimum of three years of hands-on experience deploying data science and machine learning models into live production environments, ensuring real-world impact.
• 🐍Master Python & ML Frameworks: Demonstrate deep proficiency in Python and leading ML frameworks like PyTorch, TensorFlow, and Scikit-learn, enabling rapid model development and iteration.
• 🧠Apply ML Fundamentals: Leverage a strong understanding of machine learning fundamentals, deep learning architectures, and statistical modeling to build innovative and accurate solutions.
• ☁️Utilize Cloud & Containerization: Employ cloud computing platforms (AWS, GCP, or Azure) and containerization technologies (Docker) to build scalable and efficient ML pipelines.
• 💡Solve Problems & Innovate: Apply a proactive problem-solving mindset, sharp analytical skills, and unwavering passion to develop impactful ML solutions that drive business results.