264 geprüfte Jobs in der KI-Entwicklung

Über das Unternehmen

Looking For: - Data engineering at ML scale. You have 5+ years in data engineering on a modern stack, with proven experience handling systems that process several TB of data per day and thousands of events per second. - Flink is your default for real-time. You have hands-on experience with Apache Flink for stateful stream processing and real-time feature computation.

You ll translate Data Science requirements into high-performance streams, enable Data Scientists to contribute new features and implement features yourself when needed. - Pipeline bottlenecks don t survive long around you. You know how to identify and eliminate inefficiencies in complex ETL jobs, whether handling high-volume batch processing or real-time streaming systems like Kafka. At adjoe, data velocity is critical: slow pipelines directly impact model freshness and prediction quality at sub-100ms inference. - You think in layers, not tables.

You move beyond raw data to design robust, multi-layered data architectures using dbt, and can reason confidently about storage formats, Data Lakehouse models, and what belongs where in a 1PB+ data lake. Familiarity with Medallion Architecture is a strong plus. - The bridge between Data Science and Backend. You ve worked closely with Data Scientists on online ML systems with low latency requirements, and understand what it takes to make experimental research production-ready.

Strong Java required; Go or Python a plus. - Owns quality, not just delivery. You implement data validation, monitoring, and governance processes in production, because in a system where model inputs directly drive advertiser ROI, data integrity isn t optional. Experience with Airflow, Kubeflow, AWS, Terraform, and Kubernetes is a strong plus.

We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team. What’s in It for You? 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.

Zur Position

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. 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.

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.

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. The data infrastructure behind this runs at real scale: 2TB ingested in real time every day, 100+ Airflow jobs and data pipelines, and ML models handling p99 latency of 100ms across 100,000+ predictions per second. As a Data Engineer on this team – you ll be building and maintaining the infrastructure that makes them possible: the Feature Store, the data pipelines, the data quality systems, and the data architecture that data scientists depend on to move fast.

Your Mission &