At a Glance
- Tasks: Tackle challenging ML problems and drive impactful solutions at Almedia.
- Company: Join Almedia, Europe's #3 fastest-growing company, aiming for unicorn status.
- Benefits: Enjoy a generous bonus scheme, career growth, and a supportive work environment.
- Other info: Passion for gaming and experience in adtech are a plus!
- Why this job: Make a real impact in a high-growth startup while working with cutting-edge technology.
- Qualifications: Strong ML expertise, Python and SQL mastery, and excellent communication skills.
The predicted salary is between 70000 - 90000 £ per year.
This isn’t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We’re aiming to become Germany’s second bootstrapped unicorn. Almedia is already Europe’s #3 fastest-growing company in 2025 (FT1000). We are building the future of marketing by rewarding our community of over 70 million users for engaging with our advertisers’ products. We are offering a new way to acquire users for the biggest companies in the world.
You'll take ownership of the hardest ML problems across Almedia's products and growth. This is a hands‑on role for someone who identifies what matters most, sets the technical direction, and drives it end to end with minimal oversight.
Types of problems you'll be solving:
- Designing and owning the strategy for user reward schemes at scale, across behaviour signals and market dynamics
- Architecting real-time personalisation systems for reward values that operate at production scale
- Defining how we detect and diagnose underperforming campaigns, and building the systems that act on it
Your role:
- Own end-to-end delivery of high-impact ML systems: from problem framing through to production and iteration
- Set the technical bar for ML across the org, establishing best practices and raising the quality of decisions
- Define where ML creates the most business value and align the roadmap accordingly
- Apply advanced statistical and causal inference methods with rigour and production-readiness
- Partner with product and engineering leadership to shape how technical capability maps to strategic priorities
You have:
- A strong track record of taking ambiguous, high-impact problems from first principles to production independently
- Deep expertise in statistics, causal inference, and experimentation at scale
- Mastery of Python and SQL, with extensive hands‑on cloud and production systems experience
- A history of setting technical direction and raising the bar for engineering teams around you
- The communication range to influence both engineers and senior business stakeholders
Bonus points for:
- Passion for gaming and a strong intuition for player behaviour
- Experience in adtech, monetisation platforms, or the gambling industry
- Familiarity with gaming KPIs such as pLTV, retention, and ROAS
Why Almedia?
- Scale With Almedia: Have a real impact and grow alongside a startup that has been profitable from day one.
- High‑Growth Environment: We encourage all staff to take ownership of projects and consistently raise the bar.
- Do More, Get More: Generous bonus scheme to ensure great, proactive work is valued.
We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer. We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.
Principal Machine Learning Engineer employer: ALmedia
At Almedia, we are not just building a company; we are creating a movement in the marketing landscape. As a Principal Machine Learning Engineer, you will thrive in our high-growth environment where your contributions directly impact our trajectory towards becoming Germany’s second bootstrapped unicorn. With a commitment to employee growth, a generous bonus scheme, and a culture that celebrates diversity and innovation, Almedia offers an unparalleled opportunity for those eager to push boundaries and accelerate their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Machine Learning Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like ALmedia!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Principal Machine Learning Engineer at ALmedia.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like ALmedia.
✨Apply Directly through Our Website
When you find a suitable opening like Principal Machine Learning Engineer at ALmedia, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Principal Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at ALmedia, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ALmedia. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at ALmedia
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at ALmedia!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
