Machine Learning Engineer (f/m/d)

adjoe is a leading mobile ad platform developing cutting-edge advertising and monetization solutions that take its app partners’ business to the next level. Part of the applike group ecosystem, adjoe is home to an advanced tech stack, powerful financial backing from Bertelsmann, and a highly motivated workforce to be reckoned with.

Meet Your Team: Programmatic Data Science

Did you know that in-app ads are sold in a real-time auction before they get rendered in thousands of mobile apps? Dozens of ad networks compete for every single view, choosing their best ad and deciding what price to bid in just a couple hundred milliseconds. We at adjoe have developed our own ad network that takes part in this competition, going against giants like Google, Meta and TikTok to present its own ads.

In the competitive real-time bidding landscape, the Programmatic Data Science team operates at a rapid pace, developing cutting-edge algorithms, to create systems that outperform industry giants. Our approach is deeply rooted in rigorous research into user behavior, publisher and advertiser objectives, ensuring an optimal user experience. We are a fast-moving team that rapidly translates theory into impactful solutions, using state-of-the-art technologies and collaborating closely with product and business stakeholders.

What You Will Do:

• Architect and deploy a high-throughput, low-latency recommendation system capable of scaling to millions of users and billions of daily requests.
• Leverage Large Scale Dataset: identify relevant signals to improve model performance.
• Develop and refine relevance models, bidding strategies, using advanced machine learning techniques, directly influencing the company revenue.
• Own the end2end lifecycle of production machine learning models, including rigorous monitoring, in-depth performance analysis, and data-driven iterative improvements.
• Collaborate closely with backend engineering teams to design and implement robust, scalable, and production-ready machine learning solutions, ensuring seamless integration and industrialization of reusable models and assets.
• Conduct rigorous A/B testing and experimentation, Validate your hypothesis and measure the impact of new features on key business metrics.

Who You Are:

• You have 2+ years of proven experience developing and deploying production-grade recommendation systems in a high-volume environment (e.g., adtech, e-commerce, search).
• You demonstrated expertise in deep learning, with hands-on experience building and optimizing neural network architectures for recommendation tasks using TensorFlow, PyTorch or Jax.
• You are a software engineer at heart.
• Plus: you have understanding of data engineering principles
• Plus: experience working with large-scale distributed data processing systems (e.g., Spark, Flink, Kafka) and data storage solutions (e.g., AWS Athena, S3, MySQL).

Fuel for the Journey: Benefits to Support Your Ambitions

• Invest in Your Future: Regular feedback and our development program support your growth, helping you expand your skill set and achieve your career goals.
• Easy Arrival to adjoe: From signing to settling in Hamburg, we’ve got you covered. Need a visa? No problem. Ready to build your new life and career at adjoe in Hamburg? We support every ambition—from learning German to a relocation bonus that helps you settle in and make Hamburg feel like home.
• Live Your Best Life, at Work and Beyond: We work in a hybrid setup with 3 core office days, plus flexible working hours. Enjoy 30 vacation days, 3 weeks of remote work per year, and free access to an in-house gym with lots of different fitness classes and mental health support through our Employee Assistance Program (EAP).
• Thrive Where You Work: Enjoy the Alster lake view from our central office with top-notch equipment, fun open spaces, and a large variety of snacks and drinks.
• Join the Community! Participate in regular team and company events, including hackathons and social gatherings. We work together, and we celebrate together, too.