adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually. Architecting Intelligence to Optimize 200M+ Daily Decisions. As the intelligence core of our engineering organization, our Data Science team doesn't just deploy models, we engineer the fundamental decision engine that powers our platform
We aren't just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange. Engineered for performance, our stack leverages Tensorflow and PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation
Your Mission & Who We Are Looking For
Задачи
Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem
Требования
Proven track record in production ML
You have 5+ years in Data Science with a history of deployed models that moved real business metrics, not just research that stayed in notebooks
At adjoe, you'll be building models that predict LTV, conversion, and user behavior across 770 million users, directly impacting advertiser ROAS and publisher revenue
Deep learning is your primary tool
You have strong hands-on experience with PyTorch or TensorFlow and have deployed deep learning models in production environments handling 1M+ daily predictions
You know the difference between a model that works in evaluation and one that holds up under real traffic
Full ML lifecycle ownership
You own the problem end-to-end from extracting insights out of terabytes of behavioral data using Trino, Spark, or AWS Athena, through model development and A/B validation, to production deployment
Experience with Airflow or model hosting is a strong plus
Fluent in both Python and data at scale
You work comfortably with the core DS stack (pandas/polars, numpy, scikit-learn, LightGBM, CatBoost, XGBoost) and have advanced SQL skills for drilling into large distributed datasets
Bridges ML and product
You can translate product requirements into ML logic and explain model behavior and impact to non-technical stakeholders without losing the technical depth underneath
AdTech experience is a strong plus
Условия
We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team
At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech
The systems you work on will reach hundreds of millions of users and power billions of decisions every day
Go Big. Own projects with impact on 770M users and push adtech boundaries
Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum
Be Direct. Solve problems openly and collaborate across teams
Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other
Have Fun. Celebrate wins, enjoy daily victories, and bring your energy
We welcome applications from people who will contribute to the diversity of our company
At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time
Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision
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ashbyОсновная публикация · 2026-05-22
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