Senior Machine Learning Engineer - Applied ML & Research
Senior Machine Learning Engineer - Applied ML & Research

Senior Machine Learning Engineer - Applied ML & Research

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Develop 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, international environment with a commitment to diversity and responsibility.
  • Why this job: Make a real impact on millions of users with innovative ML technologies.
  • Qualifications: 4+ years in ML, strong Python skills, and a passion for problem-solving.

The predicted salary is between 60000 - 80000 £ 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!

As a Senior 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. 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:

  • 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 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.

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.

Senior Machine Learning Engineer - Applied ML & Research employer: Super Technologies

Super is an exceptional employer that champions innovation and collaboration, making it a prime choice for those looking to make a significant impact in the gaming and technology sectors. With a commitment to employee growth, a diverse and inclusive work culture, and a focus on responsible practices, Super offers a dynamic environment where talented individuals can thrive and contribute to shaping the future of entertainment. Located across multiple countries, including the UK, employees benefit from a truly international experience while working on cutting-edge machine learning solutions that enhance user experiences for millions.
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Contact Detail:

Super Technologies Recruiting 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 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 your experience aligns with the role.

✨Tip Number 4

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 mission to revolutionise play!

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
Model Evaluation
Deployment
Monitoring
Training/Inference Pipelines
Code Quality
Documentation
Problem-Solving Skills
AWS Services (e.g., EC2, EKS)

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your proficiency in Python, ML libraries, and any relevant projects you've worked on that showcase your problem-solving skills.

Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about machine learning and how you can contribute to our mission at Super. Be specific about your experience with ML systems and how it relates to the role.

Showcase Your Projects: If you've contributed to open-source ML projects or have hands-on experience with AWS services, make sure to mention these in your application. We love seeing real-world applications of your skills!

Apply Through Our Website: We encourage you to apply directly through our careers page. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!

How to prepare for a job interview at Super Technologies

✨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 understanding and practical experience.

✨Showcase Your Coding Skills

Prepare to demonstrate your coding abilities in Python, particularly with ML libraries like PyTorch and XGBoost. You might be asked to solve a problem on the spot, so practice writing clean, maintainable code and be ready to explain your thought process.

✨Communicate Clearly

Since you'll need to communicate model behaviour and results to both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will help you stand out as someone who can bridge the gap between different teams.

✨Familiarise Yourself with Tools

If you have experience with ML tooling like MLflow or cloud services like AWS, make sure to highlight that. Even if you haven't used them extensively, showing a willingness to learn and adapt can impress interviewers.

Senior Machine Learning Engineer - Applied ML & Research
Super Technologies

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