Super
Staff Machine Learning Engineer - Applied ML & Research

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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
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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.


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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.
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