Machine Learning Engineer

16 hours ago

Prague, Hlavní město Praha, Czech Republic Oddin Full time 1,200,000 - 2,400,000 per year
At , 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.
Haven't we caught you yet?
Help us maintain our position as the No. 1 esports analytics company with the new focus on AI-powered video. Imagine a culture that embraces change and quickly adapts to global opportunities. Experience immense potential for personal growth while contributing to an innovative team. Work remotely or in a hybrid style – whatever suits you best. Enjoy our brand new Norse-myth-inspired offices in Prague. Improve your English with company-sponsored language courses. Participate in quarterly team-building activities to bond with your team. Benefit from a sponsored Multisport card.
Ready to become one of us?

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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