United Kingdom
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 aStaff Machine Learning Engineerin ourApplied ML & Research team, you’ll drive the development of cutting‑edge 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 in the organization through cross‑functional collaboration.
What you’ll you be doing:
- Identify high‑impact ML opportunities and influence stakeholders to prioritize 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 technical best practices as well as alignment with business goals.
- Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.
We’re looking for someone with:
- 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 inPython(with libraries likePyTorch, XGBoost, Scikit‑learn) andSQL.
- Strong experience with machine learning pipelines and orchestration tools such asAirflow,SageMaker Pipelines, or similar.
- Deep understanding of machine learning fundamentals, including experience withLarge 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 ability to scope and disambiguate complex ML projects into clear, achievable milestones.
- Familiarity with ML tooling such asMLflow,ZenML, orMetaflow.
- Hands‑on experience withAWSservices (e.g., EC2, EKS, CloudFormation, Cognito).
- Exposure to streaming data platforms like Kafka.
- Contributions to open‑source ML projects or publications in ML conferences.
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.
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