Senior Machine Learning Operations Engineer

2 Months ago • 5 Years + • Research Development

Job Summary

Job Description

As a Senior MLOps Engineer at Easygo, you'll lead the design, implementation, and maintenance of end-to-end ML infrastructure and automation solutions. This includes building robust, scalable AWS cloud infrastructure, implementing CI/CD pipelines for ML workloads, and optimizing monitoring and alerting. You'll work with petabyte-scale data, impacting millions of users, collaborating closely with data scientists and stakeholders. Mentorship of junior engineers and promoting best practices are also key responsibilities. The role involves leveraging Terraform, containerization technologies (Docker, Kubernetes), and Python for infrastructure automation.
Must have:
  • 5+ years MLOps/DevOps experience
  • AWS cloud infrastructure expertise
  • Terraform proficiency
  • CI/CD pipeline building (ML)
  • Docker/Kubernetes experience
  • Advanced Python scripting
Good to have:
  • iGaming experience
  • Petabyte-scale data experience
  • Spark/Hadoop experience
  • Monitoring/observability platform knowledge
  • Data security/governance knowledge
Perks:
  • EAP access
  • Learning & Development platform
  • Paid volunteer day
  • Free coffee/tea/juices/smoothies
  • Free daily breakfast
  • Massage Wednesdays
  • Team lunches/Friday happy hour
  • Fun office environment
  • Cold drinks/snacks

Job Details

Passionate about building and deploying Machine Learning pipelines at scale to drive business value? Join our growing Data Science Team as our first Senior Machine Learning Operations (MLOps) Engineer!

What's in it for you?

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.

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.

Who are we?
At Easygo we proudly stand as a prominent service provider to a powerhouse of brands within the iGaming 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 500+, 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!

What you will do:

  • 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.

What you will bring: 

Essential experience

  • 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.

Bonus points if you also have:

  • 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.

Some of the perks of working for us:

  • EAP access for you and your family
  • Access to over 9,000 courses across our Learning and Development Platform 
  • Paid volunteer day
  • Two full-time baristas who will make your daily coffee, tea, fresh juices and smoothies for FREE!
  • FREE daily catered breakfast!
  • Massage Wednesdays - we get professionals to do this!
  • Team lunches and happy hour in the office from 4pm on Fridays
  • Fun office environment with pool tables, table tennis and all your favourite gaming consoles
  • 'Help Yourself' Cold Drinks Fridges and massive Snack Walls on every working level!

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 experience we never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. We are passionate about providing a workplace that encourages great participation and an equal playing field, where merit and accomplishment are the only criteria for success.

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