Staff Machine Learning Engineer - Applied ML & Research United Kingdom in London
Staff Machine Learning Engineer - Applied ML & Research United Kingdom

Staff Machine Learning Engineer - Applied ML & Research United Kingdom in London

London Full-Time 70000 - 90000 ÂŁ / year (est.) No home office possible
Superbet Foundation

At a Glance

  • Tasks: Drive development of cutting-edge machine learning solutions for online gaming platforms.
  • Company: Join a global tech group revolutionising entertainment and fan experiences.
  • Benefits: Competitive salary, diverse team, and opportunities for professional growth.
  • Other info: Dynamic environment with a focus on collaboration and continuous improvement.
  • Why this job: Make a real impact on millions of users with innovative ML technology.
  • Qualifications: Master’s degree in relevant field and 7+ years of industry experience.

The predicted salary is between 70000 - 90000 ÂŁ per year.

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 our Applied 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 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 in Python (with libraries like PyTorch, XGBoost, 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 ability to scope and disambiguate complex ML projects into clear, achievable milestones.
  • 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 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.

Staff Machine Learning Engineer - Applied ML & Research United Kingdom in London employer: Superbet Foundation

At Super, we are committed to fostering a dynamic and inclusive work culture that empowers our employees to innovate and excel. As a Staff Machine Learning Engineer, you will not only have the opportunity to work on cutting-edge technology that shapes the future of entertainment but also benefit from a collaborative environment that prioritises professional growth and mentorship. With a global presence and a diverse team, we offer unique advantages such as exposure to international markets and the chance to make a significant impact on millions of users worldwide.
Superbet Foundation

Contact Detail:

Superbet Foundation Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Machine Learning Engineer - Applied ML & Research United Kingdom in London

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the crowd.

✨Tip Number 3

Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects in detail. Practice common ML interview questions and think about how you can relate your experience to the role you're applying for.

✨Tip Number 4

Apply through our website! We love seeing applications directly from candidates who are excited about what we do. Tailor your application to highlight how your skills align with our mission and the specific role.

We think you need these skills to ace Staff Machine Learning Engineer - Applied ML & Research United Kingdom in London

Machine Learning
Data Science
Statistics
Mathematics
Computer Science
Python
PyTorch
XGBoost
Scikit-learn
SQL
Machine Learning Pipelines
Airflow
SageMaker Pipelines
Large Language Models (LLMs)
AWS Services

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the role of Staff Machine Learning Engineer. Highlight your experience with ML models, Python, and any relevant projects that showcase your skills. We want to see how you can contribute to our mission!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background aligns with our goals at StudySmarter. Keep it engaging and personal – we love to see your personality!

Showcase Your Projects: If you've worked on any interesting ML projects, make sure to mention them in your application. Whether it's open-source contributions or personal projects, we want to see what you've done and how it relates to the role.

Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you're keen on joining our team!

How to prepare for a job interview at Superbet Foundation

✨Know Your ML Fundamentals

Brush up on your machine learning fundamentals before the interview. Be ready to discuss concepts like classifiers, regressors, and the full ML lifecycle. This will show that you have a solid foundation and can handle the technical challenges of the role.

✨Showcase Your Projects

Prepare to talk about specific projects where you've built and deployed ML models at scale. Highlight your contributions, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.

✨Understand Their Tech Stack

Familiarise yourself with the tools and technologies mentioned in the job description, such as Python libraries, AWS services, and ML orchestration tools. Being able to discuss these in detail will show that you're not just a fit for the role but also genuinely interested in their tech environment.

✨Prepare for Cross-Functional Collaboration

Since the role involves influencing stakeholders and guiding technical direction, think of examples where you've successfully collaborated with non-technical teams. Be ready to explain how you translated complex concepts into clear insights for different audiences.

Staff Machine Learning Engineer - Applied ML & Research United Kingdom in London
Superbet Foundation
Location: London

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