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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: 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: 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. Some of the perks of working with us: 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.