Senior Machine Learning Operations Engineer (MLOps)

As a Senior MLOps Engineer, you will work within our collaborative Data Science team to help deliver and accelerate multiple machine learning projects across our organisation.

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.

At Easygo we proudly stand as a prominent service provider to a powerhouse of brands within the entertainment industry, including Stake.com, Kick.com and Twist Gaming. 

Stake is the world's largest crypto casino, and leads the industry with a seamless online casino and sportsbook experience.

Level up your online entertainment with Kick.com, the vibrant live-streaming platform, which connects millions of gamers and content creators worldwide.

All alongside the innovative game design studio, Twist Gaming, which takes creativity to new heights by crafting cutting-edge and captivating games. 

Our commitment to placing our clients and their communities' entertainment at the forefront of everything we do, has solidified us as the ultimate online service provider for entertainment companies.

Headquartered in the beautiful city of Melbourne, our growth has been remarkable. From humble beginnings to a thriving workforce of 700+, we've expanded not only in numbers but in ambition. There really is something for everyone here, whether you work in Tech, Marketing, Operations, Mathematics or Design, we are sure to have something for everyone.

Click play, on your career today!

• →Lead the design, implementation, and maintenance of end-to-end ML infrastructure and automation solutions, from: development, to deployment and production monitoring.
• →Drive cloud infrastructure and architectural decisions supporting large-scale ML workloads, leveraging Infrastructure as Code (IaC), particularly using Terraform. 
• →Implement and maintain CI/CD pipelines, ensuring efficient model integration, deployment, and continuous delivery.
• →Build and optimise monitoring, alerting and logging to ensure model reliability, performance and compliance.
• →Collaborate closely with data scientists and stakeholders to identify infrastructure needs, streamline workflows, and effectively communicate complex technical concepts.
• →Provide mentorship and technical guidance to junior MLOps engineers and data scientists to promote best practices in ML infrastructure.

• 5+ years of experience in MLOps, DevOps, Data Engineering and/or cloud infrastructure roles, preferably supporting data science or Machine Learning teams.
• 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.

• Experience within iGaming.
• Experience working with large volumes of data, preferably at petabyte-scale.
• Extensive experience with distributed computing and big data technologies (e.g. Spark, Hadoop).
• Familiarity with monitoring and observability platforms.
• Knowledge of data security, governance, and compliance practices relevant to ML operations.