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.
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.
Essential Experience — What you will bring
* 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 Joining Us
* Access to over 9,000 courses across our Learning and Development Platform.
* EAP access for you and your family.
* Be rewarded with lucrative annual bonuses.
* Paid volunteer day.
* Daily breakfast and open pantry with unlimited snacks and refreshments.
* On-site remedial massage on Wednesdays.
* In-house full-time barista providing daily coffee needs.
* Weekly team lunches and happy hour in the office from 4pm on Fridays.
* Option for up to 2 days work from home per week.
* Fun office environment with F1 simulators, table tennis and gaming consoles.
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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