Job
- Level
- Senior
- Job Feld
- Data, Back End
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In dieser Rolle entwickelst du autonome ML-Systeme und orchestrierst Datenpipelines für Echtzeitanwendungen, während du Produktions-ML-Services baust und wartest sowie Integrationen mit externen APIs durchführst.
Job Technologien
Deine Rolle im Team
- We are on a lookout for a hands-on Principal ML Engineer (Agentic AI) to join the Vendor Data Team on our journey to always deliver amazing experiences to go beyond prompt engineering into autonomous orchestration: designing agents that generate their own prompts, tools that empower AI with real-world actions, and judge models that validate outputs.
- Your work won't sit in research notebooks - it'll ship.
- The Agentic AI team is building the next generation of AI-native products - intelligent systems that reason, act, and adapt.
- We combine the power of large language models (LLMs), autonomous agents, and retrieval-augmented generation (RAG) to move beyond static prompts and chatbots into dynamic AI systems that solve real problems at scale.
- We don't treat LLMs as tools to micromanage - we treat them as collaborators.
- Our products are designed to build and evolve themselves, leveraging AI to orchestrate workflows, make decisions, and continuously improve.
- If you're ready to stop building brittle bots and start building AI that builds AI - this is your playground.
- 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.
- Establish monitoring, evaluation, and observability frameworks across data, models, and systems, while mentoring engineers and setting technical direction.
Unsere Erwartungen an dich
Qualifikationen
- Deep expertise in data engineering and ML pipelines, including feature/data pipelines, RAG systems, and embedding workflows.
- Familiarity with synthetic data generation, evaluation systems, or AI feedback loops.
- Knowledge of system reliability, failure handling, and safety patterns in AI systems.
Erfahrung
- Strong experience designing and scaling production-grade ML systems and data platforms, including large-scale deployments.
- 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.).
- 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.
Unser Angebot
- Ensuring you and all our Heroes are looked after, happy, and healthy is always on the menu.
- Make the most of our hybrid working model and join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week.
- We offer 27 days holiday with an extra day on 2nd and 3rd year of service.
- We will support you in developing yourself and your career growth opportunities: 1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform to explore a variety of online courses.
- Get moving and release those wonderful, mind-boosting endorphins: Health Checkups, Meditation, Yoga, Gym & Bicycle Subsidy.
- Cash. Dough. Cheddar. Whatever you call it, we'll help you with it: Employee Share Purchase Plan, Sabbatical Bank, Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan.
- The power of getting together over some food is unrivaled. Here are a few ways to help you do that. All the yum: Digital Meal Vouchers, Food Vouchers, Corporate Discounts.
Benefits
Essen & Trinken
Work-Life-Integration
Gesundheit, Fitness & Fun
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Delivery Hero SE
Niklas Östberg gründete Delivery Hero im Mai 2011 und startete seine Reise, um ein führendes global agierendes Unternehmen im Bereich Online-Essensbestellungen aufzubauen. Sein Gründungsteam, das mit Mitgliedern von Team Europe vervollständigt wurde, teilte sich Jahrzehnte an Wissen über die Arbeit mit Internetunternehmen. Genauso wichtig war jedoch, dass sie eine Vision für die Zukunft der Online-Essensbestellung teilten. Gemeinsam mit einem ausgewählten und leidenschaftlichen Team gelang es ihnen tatsächlich, das Geschäft auf die heutige Stufe zu katapultieren.
Description
- Gründungsjahr
- 2011
- Sprachen
- Englisch
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Handel
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Principal ML Engineer
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
