Principal ML Engineer (Agentic AI)-Vendor Data Team

Position

Principal Machine Learning Engineer (Agentic AI) – Vendor Data Team

About the Role

You will be the driving force behind the success of thousands of restaurants, shops, and local businesses. Your contributions will empower vendors with advanced tools to manage their operations, boosting their visibility and reach. Every feature you help build will create growth opportunities for businesses of all sizes, strengthening Delivery Hero’s ecosystem and impact.

Key Responsibilities

• Design and own end‑to‑end ML and data systems from ingestion and transformation to model integration and production deployment.
• Architect and maintain scalable data pipelines for RAG, embeddings, and real‑time/near‑real‑time data processing.
• Build and operate production‑grade ML services and APIs, ensuring reliability, scalability, and performance.
• Define standards for infrastructure, deployment, and system reliability, including Infrastructure as Code, containerization, and orchestration.
• Integrate ML systems with external APIs, tools, and operational platforms, enabling real‑world actions and automation.
• Lead the implementation of security best practices for AI systems, including secure prompt handling, data privacy protocols, and protection against adversarial attacks or model injection. Ensure all AI agents operate within strict authorization boundaries.

Required Qualifications

• Strong experience designing and scaling production‑grade ML systems and data platforms, including large‑scale deployments.
• Deep expertise in data engineering and ML pipelines, including feature/data pipelines, RAG systems, and embedding workflows.
• Proven experience building and maintaining reliable data infrastructure with strong guarantees around data quality and freshness.
• Strong engineering skills in Python and SQL, with experience in Docker, Kubernetes, and cloud environments.
• Experience with Infrastructure as Code (e.g., Terraform or similar) and building reproducible, scalable systems.
• Hands‑on experience integrating ML systems with real‑world APIs and services, and operating them in production with monitoring and observability.

Nice to Have

• Experience with LLMs, agent architectures, or orchestration frameworks (LangGraph, AutoGen, CrewAI, etc.).
• Familiarity with synthetic data generation, evaluation systems, or AI feedback loops.
• Experience with agent or ML observability tools such as Langfuse or LangSmith.
• Experience with model serving, routing, or inference optimization.
• Experience with open‑source models (e.g., LLaMA, Mistral, Mixtral) or custom inference stacks.
• Knowledge of system reliability, failure handling, and safety patterns in AI systems.

Benefits (Some of the highlights)

• Hybrid working model – 2 days a week on the Berlin campus.
• 27 days holiday with an additional day on the second and third year of service.
• Educational budget of €1,000, language courses, parental support and access to Udemy Business.
• Health program: check‑ups, meditation, gym access.
• Employee Share Purchase Plan, Sabbatical Bank, public transport discount, life & accident insurance, corporate pension plan.
• Meal vouchers, food vouchers, corporate discounts.
• Relocation support for Berlin with dedicated hub and information.

Equal Opportunity & Diversity

Delivery Hero is an equal opportunity employer. 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 status, or any other aspect that defines you. Severely disabled applicants with equal qualifications will be given preferential consideration. You are welcome to share your pronouns (he/she/they) from the start so we can address you respectfully from our first contact.

We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience. Please email our Inclusion Officer at