Machine Learning Engineer - Sports Tech Experience

We are looking for a passionate and skilled Machine Learning Engineer to join our team. The ideal candidate should have a strong grasp of machine learning algorithms and practical experience implementing them in real-world applications. A deep interest in sports, especially fantasy sports, will be a major plus, as many of our projects are built around sports data and user behavior analytics. Key Responsibilities: Design, build, and deploy robust ML models to solve real-world problems Work with large and complex datasets to extract insights and optimize performance Collaborate with data engineers, product managers, and developers to integrate ML models into production Continuously improve model performance and reliability through experimentation and tuning Stay up-to-date with the latest advancements in ML/AI and apply them where relevant Requirements: Strong knowledge of machine learning algorithms, data preprocessing, and model evaluation Hands-on experience with Python and ML libraries like scikit-learn, TensorFlow, PyTorch, etc. Solid understanding of statistics, probability, and optimization techniques Experience working with real-world datasets, including cleaning, transforming, and feature engineering Ability to work independently and take ownership of projects A genuine passion for sports – familiarity with fantasy sports is a big advantage Nice to Have: Experience with recommendation systems, predictive modeling, or NLP Familiarity with deployment frameworks and cloud platforms (AWS, GCP, etc.) Contributions to open-source or ML competitions (e.g., Kaggle)