iGaming - Machine Learning Engineer

Model Development: Design, build, and maintain scalable machine learning models and algorithms.

- Data Analysis: Analyze and preprocess data from various sources to prepare it for model training.

- Model Training & Evaluation: Train, validate, and tune machine learning models to achieve optimal performance.

- Deployment: Deploy models into production and integrate them with existing systems.

- Monitoring & Maintenance: Monitor model performance in production and update models as necessary to ensure they remain accurate and relevant.

- Collaboration: Work with cross-functional teams, including data scientists, software engineers, and product managers, to understand requirements and deliver solutions.

- Research: Stay current with the latest developments in machine learning and AI to continuously improve our technology stack.

SKILLS

Proficient in programming languages like Python, Go, and Java. Experienced with popular machine learning tools and libraries such as TensorFlow, PyTorch, JAX, and scikit-learn. Skilled in handling and processing large datasets using tools like SQL, Hadoop, and Spark. Well-versed in data analysis and visualization with tools like NumPy, Pandas, and Matplotlib. Also familiar with natural language processing (NLP), including working with large language models and modern techniques like transformers and attention mechanisms.