Senior Machine Learning Engineer - Applied ML & Research

Senior Machine Learning Engineer - Applied ML & Research

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Happening

At a Glance

  • Tasks: Drive development of cutting-edge machine learning solutions for online gaming platforms.
  • Company: Join a global tech company shaping the future of entertainment.
  • Benefits: Competitive salary, remote work options, and opportunities for professional growth.
  • Other info: Dynamic team environment with global reach and ambitious growth plans.
  • Why this job: Make a real impact on user experience and platform security with innovative ML solutions.
  • Qualifications: 4+ years in ML systems, strong Python skills, and a degree in a related field.

The predicted salary is between 60000 - 80000 £ per year.

As a Senior Machine Learning Engineer in our Applied ML & Research team, you will 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. You will 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:

  • Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact.
  • Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule‑based components).
  • Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring.
  • Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability.
  • Communicate model behavior, trade‑offs, and results clearly to both technical and non‑technical stakeholders.
  • Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices.

We’re looking for someone with:

  • Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus).
  • 4+ years of industry experience building and deploying ML systems.
  • Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL.
  • Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
  • Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices.
  • Strong problem‑solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively.

Bonus points for:

  • 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.

About Us: We are a global technology company dedicated to building the future of entertainment and fan‑centric experiences. With commercial markets in Brazil, Belgium, Poland, Romania, and Serbia, our company has evolved from a leading sports betting and gaming operator into a diversified product and tech organization, gathering more than 5,000 dedicated people across our teams.

Shaping the future of play: At Super, we are creating a unique entertainment ecosystem engaging millions of customers worldwide. Our product and technology teams in Amsterdam (the Netherlands), Madrid (Spain), Zagreb (Croatia), London (UK), and Bucharest (Romania) are building the playstack that will champion the future of play. Our ambitious growth strategy focuses on expanding across Europe and Latin America while delivering immersive customer experiences and creating lasting value for our customers, partners, and communities.

Global recognition and standards: The company’s long‑term strategy is supported by world‑class investors. In 2019, Blackstone, the world’s largest alternative asset manager, made a strategic minority investment of €175 million. In 2025, we strengthened our financial position through a €1.3 billion refinancing agreement, reinforcing our partnership with Blackstone and enabling accelerated global expansion. 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).

Senior Machine Learning Engineer - Applied ML & Research employer: Happening

As a remote employer, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. With a strong focus on professional growth, we offer ample opportunities for skill development and career advancement, all while working alongside industry leaders in the exciting field of sports betting. Join us to make a meaningful impact in a fast-paced environment where your contributions directly shape the future of gaming products.

Happening

Contact Details:

Happening Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Machine Learning Engineer - Applied ML & Research

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 refer you directly.

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 interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.

We think you need these skills to ace Senior Machine Learning Engineer - Applied ML & Research

Machine Learning
Python
ML Libraries (e.g., PyTorch, XGBoost)
SQL
Large Language Models (LLMs)
Data Exploration
Feature Engineering

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with ML systems, Python proficiency, and any relevant projects that showcase your skills in building and deploying machine learning solutions.

Showcase Your Projects:Include specific examples of your work with machine learning models, especially those involving LLMs or other emerging technologies. This will help us see your hands-on experience and how you approach problem-solving in real-world scenarios.

Be Clear and Concise:When writing your cover letter, be clear about why you want to join our Applied ML & Research team. Use straightforward language to explain your passion for machine learning and how you can contribute to our mission of enhancing user experience and platform security.

Apply Through Our Website:We encourage you to apply through our website for a smoother application process. This way, we can easily track your application and ensure it reaches the right people in our team!

How to prepare for a job interview at Happening

Know Your ML Fundamentals

Brush up on your machine learning fundamentals, especially around classifiers, regressors, and LLMs. Be ready to discuss how you've applied these concepts in real-world scenarios, as this will show your depth of knowledge and practical experience.

Showcase Your Coding Skills

Prepare to demonstrate your coding abilities in Python and your familiarity with ML libraries like PyTorch and XGBoost. You might be asked to solve a problem on the spot, so practice writing clean, maintainable code that adheres to best practices.

Communicate Clearly

Since you'll need to explain model behaviour and trade-offs to both technical and non-technical stakeholders, practice articulating complex ideas in simple terms. This will help you stand out as someone who can bridge the gap between tech and business.

Be Ready for Problem-Solving

Expect to tackle ambiguous problems during the interview. Prepare examples of how you've broken down complex issues into manageable tasks and iteratively delivered solutions. This will highlight your strong problem-solving skills and adaptability.