
// Open Role at Easygo Gaming
Lead the design and implementation of robust, scalable ML infrastructure for a leading entertainment service provider, impacting millions of users globally in gaming and streaming.
Who are we?
Easygo is the engine behind some of the entertainment industry's biggest brands, including Stake.com Kick.com Stake Engine and Easygo Games.
Easygo is the force behind brands with global reach, through products and platforms people actually choose to experience.
We do what’s exciting, not expected. That means big ideas, tight execution, and teams that are trusted to ship, learn, and ship again.
Passionate about building and deploying Machine Learning pipelines at scale to drive business value?
What's in it for you?
As a Senior Machine Learning Engineer, you will work within our collaborative Data Science team to help deliver and accelerate multiple machine learning projects across our organisation.
Your role with us:
In your role with us, you will enhance our machine learning operations (MLOps), delivering: robust, scalable AWS cloud infrastructure and automation solutions, that empower our data science team. You will get the opportunity to work with petabyte-scale data across our global platforms, directly impacting millions of users.
What you will do:
Some of the perks of working with us:
Office Perks & Environment
Wellbeing & Personal Development
Team Connection & Rewards
Events & Experiences
We believe that the unique contributions of everyone at Easygo are the driver of our success. To make sure that our products and culture continue to incorporate everyone's perspectives and experiences, we never discriminate on the basis of race, religion, nationality, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status.
We’re a global team of dreamers, creators, and game-changers from every walk of life, united by a passion for entertainment that inspires the world.
We believe that the best ideas come from different perspectives, so we actively welcome and champion talent from all backgrounds, cultures, identities, and experiences. Whether you're just starting out or bringing decades of experience, your unique voice matters here.
5+ years of experience in MLOps, DevOps, Data Engineering and/or cloud infrastructure roles. Bachelor’s degree in Computer Science, Engineering, or a related technical field. Expert proficiency in cloud infrastructure management using Terraform. Deep hands-on experience with major cloud platforms (AWS, Azure or GCP). Strong experience in building and maintaining CI/CD pipelines specifically for ML workloads. Proficiency with containerisation technologies (Docker, Kubernetes). Advanced proficiency in Python and scripting for infrastructure automation.