Company Description
As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in over 70+ countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. We enable creative minds to deliver solutions that create impact within our ecosystem. We move fast, take action and adapt. No matter where you're from or what you believe in, we build, we deliver, we lead. We are Delivery Hero.
Job Description
We are looking for a Staff Machine Learning Engineer - AdTech (all genders) to join the Vendor Data tribe in our mission to deliver consistently amazing experiences.
We are looking for a talented and motivated Staff Machine Learning Engineer - AdTech (all genders) to work with best-in-class data science and AI models to drive our fundamental shift to machine learning in the Vendor vertical at Delivery Hero. You will be working with a team of ML Engineers and Data Scientists deploying advanced ML services to solve complex problems, delivering revenue for Delivery Hero at the frontline of our profitability journey.
At Delivery Hero, we are exploring the potential of AdTech to introduce people to new food they love and to enable our partners to meet their future customers at the perfect moment. We have developed a range of products to offer advertising solutions for restaurants helping them to increase their visibility and reach, improve their order conversion, and eventually drive more sales by covering the entire marketing funnel. Operating across over 50 countries around the clock, our Ad Tech connects the ideal advertiser with the ideal customer millions of times every day. In 2025, Ad Tech is a fundamental area for us on our path to profitability and is predicted to generate more than 1 billion euros in revenue for Delivery Hero; our innovative tech and product offering is the backbone of that development.
The Vendor Data tribe’s mission is to drive innovation, insight-driven decision making and to solve business problems through a culture of excellence and openness. The tribe comprises teams of skilled analysts, engineers, and scientists working together to deliver data solutions covering a host of business opportunities across all of Delivery Hero’s 70+ markets.
If you're a builder in machine learning who is hungry for a new adventure, an international workplace is waiting for you in the heart of Berlin!
Your mission:
Drive the design and evolution of large-scale machine learning systems, ensuring they align with the AdTech strategic product and business goals.
Lead cross-functional initiatives, partnering with product, engineering, and data science teams to define long-term ML roadmaps interacting with machine learning engineers across the business to influence company-wide technical direction.
Architect scalable, reliable, and cost-efficient ML infrastructure that serves as a foundation for multiple teams and use cases across the vendor organisation.
Set and uphold best practices for productionising ML, including monitoring, testing, reproducibility, and responsible AI practices.
Conduct deep technical reviews and performance optimisations of ML systems, proactively identifying improvements to efficiency, robustness, and user impact.
Mentor and provide technical guidance to engineers and data scientists, raising the overall technical bar and fostering a culture of excellence in ML engineering.
Stay ahead of industry and academic trends, evaluating and introducing emerging technologies and methodologies that can shape Delivery Hero’s future ML capabilities.
Influence stakeholder decisions by translating complex technical considerations into clear recommendations that balance innovation, impact, and risk.
Qualifications
Extensive experience in designing, deploying, and operating large-scale machine learning systems in production, with a track record of delivering high-impact solutions.
Expert knowledge of data management, storage, and caching strategies to enable performant and cost-efficient ML systems at scale.
Deep expertise with modern ML frameworks and libraries (eg TensorFlow, PyTorch) and the ability to guide adoption of best practices across diverse ML use cases.
Hands-on experience with cloud platforms and distributed infrastructure (AWS, GCP, Azure) and proficiency in containerisation and orchestration technologies (eg Docker, Kubernetes) for building resilient ML services.
Strong systems-level problem-solving skills, with the ability to balance performance, scalability, maintainability, and business impact.
Proven leadership in technical decision-making, including mentoring engineers, leading design discussions, and influencing cross-team initiatives.
Exceptional communication and collaboration skills, with the ability to partner effectively across product, engineering, and business stakeholders at all levels.
Highly Desirable:
Experience leading ML initiatives in Ad Tech or similar large-scale, real-time decisioning domains (eg ads ranking, recommendations, bidding, or personalisation).
Hands-on expertise with neural network–based models and modern architectures (eg deep learning for ranking, reinforcement learning, contextual bandits).
Proven ability to design and scale ML systems under strict latency, throughput, and cost constraints, balancing innovation with operational excellence.
Demonstrated impact in translating advanced research into production systems that drive measurable business outcomes.
Additional Information
We believe diversity and inclusion are key to creating not only an exciting product, but also an amazing customer and employee experience. Fostering this starts with hiring - therefore we do not discriminate on the basis of racial identities, religious beliefs, color, national origin, gender identities or expressions, sexual orientations, age, marital or disability statuses, or any other aspect that makes you, you. We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience—just include it in your application. You're welcome to share your pronouns (he/she/they) right from the start so we can address you respectfully from our first contact.