At a Glance
- Tasks: Design and develop impactful machine learning solutions that drive Almedia's growth.
- Company: Join Almedia, Europe's #3 fastest-growing company, aiming for unicorn status.
- Benefits: Equity options, competitive salary, transport subsidies, and modern office perks.
- Other info: Dynamic startup culture with opportunities for mentorship and career growth.
- Why this job: Be part of a revolutionary marketing future while accelerating your career.
- Qualifications: Experience in ML solutions, strong Python and SQL skills, and statistical knowledge.
The predicted salary is between 72000 - 88000 £ 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 60 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 designing, developing, and scaling impactful, production-grade ML solutions that power Almedia’s products and growth. This is a hands-on role involving active participation in code development and delivery.
Types of problems you’ll be solving:
- Designing and optimising user reward schemes based on player behaviour and market shifts
- Leading the design and implementation of solutions for personalised, real-time reward values
- Developing solutions for identifying underperforming reward campaigns and causes of failure
Your role:
- Lead end-to-end delivery: build, deploy, and optimise solutions and services at scale
- Provide technical leadership across ML projects, ensuring best practices and high-quality code
- Align technical capabilities with business priorities to unlock high-value opportunities
- Apply advanced statistical and causal inference methods to ensure robustness and reliability
- Partner with product and engineering teams to translate business challenges into predictive, data-driven solutions
You have:
- Proven expertise in building, deploying, and maintaining solutions and services in production, ideally in adtech or high-scale environments
- Deep knowledge of statistics (A/B testing, regression, probability)
- Strong programming background in Python and SQL, with hands-on cloud experience
- Ability to mentor and set technical direction for ML engineers and cross-functional peers
- Strong communication skills to influence both technical and non-technical stakeholders
Bonus points for:
- Passion for gaming and strong understanding of player behaviour
- Experience with adtech, monetisation platforms, or the gambling industry
- Familiarity with gaming KPIs such as pLTV, retention, and ROAS
Why Almedia?
- Own Our Growth: We offer all Berlin-based employees equity in Almedia to truly be a part of our success.
- Scale With Almedia: Grow alongside a startup that has been profitable from day one.
- Central Berlin Office: Work from a fully-stocked modern office built for collaboration, accessible from all around Berlin.
- Other Benefits: Transport subsidy, breakfasts and lunches, language learning, Urban Sports Club, and more.
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.
Machine Learning Engineer employer: Almedia
Almedia is an exceptional employer for Machine Learning Engineers, offering a dynamic work environment in the heart of Berlin where innovation thrives. With equity options, a collaborative office space, and a commitment to employee growth, we empower our team to take ownership of their projects while enjoying benefits like transport subsidies and wellness programs. Join us to be part of a rapidly growing company that values diversity and fosters talent at every level.
StudySmarter Expert Advice🤫
We think this is how you could land 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 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 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 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.
