iGaming - Machine Learning Engineer

Model Development: Create, implement, and sustain scalable machine learning models and algorithms.

- Data Analysis: Examine and preprocess data from diverse sources to prepare it for training models.

- Model Training & Evaluation: Train, validate, and fine-tune machine learning models to ensure peak performance.

- Deployment: Launch models into production and integrate them with current systems.

- Monitoring & Maintenance: Oversee model performance in production and update models as needed to maintain accuracy and relevance.

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

- Research: Keep abreast of the latest advancements in machine learning and AI to enhance our technology stack continuously.

SKILLS

Proficient in programming languages such as Python, Go, and Java. Experienced with leading machine learning tools and libraries including TensorFlow, PyTorch, JAX, and scikit-learn. Adept at managing and processing large datasets utilizing tools like SQL, Hadoop, and Spark. Knowledgeable in data analysis and visualization using tools like NumPy, Pandas, and Matplotlib. Additionally, familiar with natural language processing (NLP), including experience with large language models and contemporary techniques like transformers and attention mechanisms.