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Senior Machine Learning Operations Engineer

Senior Machine Learning Operations Engineer

GamblingCareers.comCity of Melbourne, Victoria, Australia
14 days ago
Job description

Senior Machine Learning Operations Engineer

Join to apply for the Senior Machine Learning Operations Engineer role at GamblingCareers.com

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

  • 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.
  • Office Perks & Environment

  • In-house baristas serving free coffee, tea, fresh juices, and smoothies
  • Daily catered breakfast and regular company-wide events
  • Snack walls and drink fridges on every floor
  • Fun / modern office spaces with pool tables, table tennis, gaming consoles, and an F1 simulator
  • Wellbeing & Personal Development

  • Access to our Employee Assistance Program for you and your loved ones
  • 9,000+ courses on our Learning & Development platform
  • One paid volunteer day per year
  • Weekly Wednesday massages by professional masseuses
  • Team Connection & Rewards

  • Team budgets for lunches and activities to celebrate achievements
  • Social sports teams and participation in Corporate Games
  • Easygo branded swag
  • Birthday and work anniversary gift vouchers, plus a chance to win prizes
  • Events & Experiences

  • Company-wide talks with key partners such as Everton FC and Team Sauber in Formula 1
  • Office visits from big-name streamers
  • Meet Ambassadors like Alex Pereira, Israel Adesanya
  • Ballots for exclusive tickets to events like Formula 1, UFC, and more sporting and music events
  • 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.

    Seniority level

  • Mid-Senior level
  • Employment type

  • Full-time
  • Job function

  • Engineering and Information Technology
  • Industries
  • Gambling Facilities and Casinos
  • Referrals increase your chances of interviewing at GamblingCareers.com by 2x

    End of description

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    Machine Learning Engineer • City of Melbourne, Victoria, Australia

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