ML Engineer (Recommender systems)

About the role:

A tech company in the sports betting and gaming analytics space is expanding its internal AI team and is looking for an ML Engineer with expertise in recommendation systems. 
You will be working on a real-time recommendation system that ranks betting options for users. Your role will involve optimizing, testing, and contributing to the development of infrastructure and evaluation pipelines to ensure high-performance recommendations.

What you'll be doing: 

• Develop, optimize, and deploy real-time recommendation systems.
• Enhance ranking models, and propose and implement new models and features.
• Design and maintain evaluation pipelines to monitor model quality.
• Optimize models for efficiency and scalability in production environments.
• Contribute to building and improving ML infrastructure for training, testing, and deployment.
• Collaborate with engineers, data scientists, and business stakeholders to refine recommendations.
• Perform A/B testing and analyze model impact on key business metrics.

Requirements:

• Strong background in recommender systems, with a focus on serving models in production.
• Proven experience in developing algorithms for recommendation engines.
• Proficiency in machine learning techniques and statistical analysis.
• Strong programming skills in Python.
• Experience working with Linux environments.
• Familiarity with recommendation system packages (e.g., Suprise, LightFM, Spotlight, Scikit-Learn).
• Experience with Pytorch.
• Experience with A/B testing methodologies to evaluate recommendation strategies.
• Strong analytical and problem-solving skills.
• Self-driven and results-oriented.

What can we offer: 

• Employment under an employment or service contract, depending on the candidate's location.
• Remote or hybrid work format.
• Flexible working hours and additional vacation days.
• Open and supportive corporate culture with a friendly atmosphere.
• Equipment provided for work.
• Development and training opportunities: language course reimbursement, access to educational programs.