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We are on a mission to pioneer the world’s next era of play. As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day. As a Staff Machine Learning Engineer in the Applied ML & Research team, you'll drive the development of machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily. This role blends hands-on technical work with strategic thinking — you'll lead by example, contribute high-quality code, and help shape the ML roadmap through cross-functional collaboration. What the role involves Identify high-impact ML opportunities and influence stakeholders to prioritise and support these initiatives Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment Translate complex technical concepts into clear insights for both technical and non-technical stakeholders Set and guide technical direction across ML projects, ensuring alignment with technical best practices and business goals Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement What we are looking for Master's degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field 7+ years of industry experience building and deploying ML models at scale Proven ability to lead cross-functional technical initiatives and influence engineering strategy Proficiency in Python (with libraries such as PyTorch, XGBoost, and Scikit-learn) and SQL Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies A track record of shipping production-level ML products and maintaining high code quality Excellent problem-solving skills and the ability to scope and disambiguate complex ML projects into clear, achievable milestones Nice to have Familiarity with ML tooling such as MLflow, ZenML, or Metaflow Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito) Exposure to streaming data platforms such as Kafka Contributions to open-source ML projects or publications in ML conferences What we offer Medical / Health Insurance Open Annual Leave Employee Assistance Programme Training & Learning Development Additional benefits vary by country and will be shared during the hiring process. About Super We are a global technology group, dedicated to building the future of entertainment and fan-centric experiences. With commercial markets in Brazil, Belgium, Poland, Romania, Greece and Serbia, and a network of offices across Spain, Croatia, Malta, Gibraltar, the Netherlands and the UK, we are a truly international organization. Our purpose at Super has evolved from sports and betting into creating the platform that stretches into the wider world of technology-driven entertainment. With a growing and diverse team of more than 5,000 people, we create immersive, responsible, and personalised experiences for millions of customers worldwide. Shaping the Future of Play Everything we do at Super is rooted in doing what is right: for customers, for each other, and for our long-term vision. Our Culture Manifesto is our North Star. It captures our purpose, mission, and the six core beliefs that shape how we think, make decisions, and act every day. Want to explore our culture in more detail? Visit our careers page: super.xyz/careers Super is committed to the highest standards of compliance, safety, and responsibility. As such, we are active members of the International Betting Integrity Association (IBIA) and the European Gaming & Betting Association (EGBA). At Super, we operate as a high-performing team. We hire and grow talent based on ability and potential, regardless of background and identity because we know diverse perspectives, drive better performance.
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.