Senior Machine Learning Engineer

About Kaizen Gaming

Kaizen Gaming, the team powering Betano, is one of the biggest GameTech companies in the world, operating in 20 markets. We always aim to leverage cutting-edge technology, providing the best experience to our millions of customers who trust us for their entertainment. We are a diverse team of more than 2.700 Kaizeners, from 40+ nationalities spreading across 3 continents. Our #oneteam is proud to be among the Best Workplaces in Europe and certified Great Place to Work across our offices. Here, there’ll be no average day for you. Ready to Press Play on Potential?

About the Role

At Kaizen, we strive to harness the power of modern AI algorithms to continuously improve our product and business. Kaizen’s AI department consists of product, platform and research teams and lies at the core of that mission. We develop AI products for various applications, ranging from detection of fraudulent activity to personalized gaming recommendations and from AI-powered co-pilots to CRM optimizations. We structure our teams to be self-driven, autonomous, and cross-functional. Within these teams, you will have the opportunity to work with Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, Product Owners and Agile Delivery Leads. As a Senior Machine Learning Software Engineer, you will focus on delivering robust and scalable Machine Learning pipelines and you will support the operationalization of Machine Learning models.

Responsibilities

• Collaborate closely with data scientists in order to deliver production-ready model training pipelines;
• Design scalable solutions in a distributed environment;
• Design scalable inference pipelines and architectures;
• Implement model diagnostics such as evaluation, monitoring flows etc.;
• Automate model deployment, enable REST API model endpoints;
• Develop scalable model serving flows;
• Work on cluster optimization and scalability;
• Develop and maintain internal tools and libraries;
• Write CI/CD/CT pipelines.

Requirements

• Extensive experience in software development using Python in large scale, high-performance production environment;
• Significant hands-on experience in designing ML software systems;
• Significant experience with cloud environments like Microsoft Azure or AWS;
• Solid understanding of:
  • The ML project lifecycle;
  • MLOps concepts and tools such as MLflow or Kubeflow;
  • ML algorithms and models.
• Hands-on experience with Spark and PySpark;
• Excellent problem solving and communication skills.