Machine Learning Engineer

Key Skills

Apache Kafka, Data science techniques, DataDog, Docker, Grafana, Kubernetes-K8s, Machine learning techniques, MLOps tools, Python Programming, RabbitMQ

Job Description

The Crown Is Yours

​Our Data Science team is composed of algorithm experts and data science technologists who leverage the power of data to deliver transformative experiences for our users and drive continued innovation. As a Machine Learning Engineer, you will be a creative thinker and utilize data, machine learning, and software development skills to craft high-impact solutions that transform our business.

What you'll do as a Machine Learning Engineer

• Integrate statistical and machine learning models into production applications

• Writing production quality code to deploy and run models in a sportsbook platform

• Utilise our MLOps platform to productionise ML workloads

• Create automatic tests to ensure model accuracy

• Collaborate closely with product, developers, and delivery leads to move projects from ideation to development and deployment

• Test that data flows work as expected and that models are well integrated in larger business context

What You'll bring

• Experience using Python, and its application to data science and data engineering

• Experience working in a cloud environment

• Experience with docker and running containerised services (e.g Kubernetes, Docker Compose)

• Experience of using observability tooling for production monitoring and alerting, such as DataDog, Grafana, Kibana

• An understanding of event driven messaging systems (e.g Kafka, RabbitMQ), ideally with real-world experience

• Experiencing with object-oriented programming

• Knowledge of infrastructure as code (e.g terraform) is also beneficial

• Understanding of data science and statistical modelling principles will be considered an asset

• Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, or a software engineering related field