Dein persönlicher KI-Karriere-Agent
Principal ML Engineer (Agentic AI)(m/w/x)
Designing and scaling end-to-end ML and data systems for a global delivery platform. Expertise in data engineering and ML pipelines required. 27 days holiday, educational budget, and language courses.
Anforderungen
- Experience designing and scaling production ML systems
- Experience designing and scaling production data platforms
- Experience with large-scale deployments
- Expertise in data engineering
- Expertise in ML pipelines
- Expertise in feature/data pipelines
- Expertise in RAG systems
- Expertise in embedding workflows
- Experience building reliable data infrastructure
- Experience maintaining reliable data infrastructure
- Strong guarantees around data quality
- Strong guarantees around data freshness
- Engineering skills in Python
- Engineering skills in SQL
- Experience with Docker
- Experience with Kubernetes
- Experience with cloud environments
- Experience with Infrastructure as Code
- Experience building reproducible systems
- Experience building scalable systems
- Experience integrating ML systems with APIs
- Experience integrating ML systems with services
- Experience operating ML systems in production
- Experience with monitoring and observability
- Experience with LLMs
- Experience with agent architectures
- Experience with orchestration frameworks
- Familiarity with synthetic data generation
- Familiarity with evaluation systems
- Familiarity with AI feedback loops
- Experience with agent observability tools
- Experience with ML observability tools
- Experience with model serving
- Experience with model routing
- Experience with inference optimization
- Experience with open-source models
- Experience with custom inference stacks
- Knowledge of system reliability patterns
- Knowledge of failure handling patterns
- Knowledge of safety patterns in AI systems
Aufgaben
- Design and own end-to-end ML and data systems
- Architect scalable data pipelines for RAG, embeddings, and real-time data
- Build and operate production-grade ML services and APIs
- Define standards for infrastructure, deployment, and system reliability
- Integrate ML systems with external APIs and operational platforms
- Lead implementation of security best practices for AI systems
- Ensure secure prompt handling and data privacy
- Protect against adversarial attacks and model injection
- Maintain strict authorization boundaries for AI agents
Berufserfahrung
- ca. 4 - 6 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- SQL
- Docker
- Kubernetes
- Terraform
- LLMs
- LangGraph
- AutoGen
- CrewAI
- Langfuse
- LangSmith
- LLaMA
- Mistral
- Mixtral
Benefits
Mehr Urlaubstage
- 27 days holiday
- Extra holiday day on 2nd year of service
- Extra holiday day on 3rd year of service
Sonstige Zulagen
- 1000 EUR Educational Budget
- Digital meal vouchers
- Food vouchers
Weiterbildungsangebote
- Language courses
- Udemy Business platform access
Familienfreundlichkeit
- Parental support
Gesundheits- & Fitnessangebote
- Health checkups
- Gym subsidy
Mentale Gesundheitsförderung
- Meditation
Firmenfahrrad
- Bicycle subsidy
Attraktive Vergütung
- Employee Share Purchase Plan
Workation & Sabbatical
- Sabbatical bank
Öffi Tickets
- Public transportation ticket discount
Sonstige Vorteile
- Life & accident insurance
Betriebliche Altersvorsorge
- Corporate pension plan
Mitarbeiterrabatte
- Corporate discounts
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Principal ML Engineer (Agentic AI)(m/w/x)
Designing and scaling end-to-end ML and data systems for a global delivery platform. Expertise in data engineering and ML pipelines required. 27 days holiday, educational budget, and language courses.
Anforderungen
- Experience designing and scaling production ML systems
- Experience designing and scaling production data platforms
- Experience with large-scale deployments
- Expertise in data engineering
- Expertise in ML pipelines
- Expertise in feature/data pipelines
- Expertise in RAG systems
- Expertise in embedding workflows
- Experience building reliable data infrastructure
- Experience maintaining reliable data infrastructure
- Strong guarantees around data quality
- Strong guarantees around data freshness
- Engineering skills in Python
- Engineering skills in SQL
- Experience with Docker
- Experience with Kubernetes
- Experience with cloud environments
- Experience with Infrastructure as Code
- Experience building reproducible systems
- Experience building scalable systems
- Experience integrating ML systems with APIs
- Experience integrating ML systems with services
- Experience operating ML systems in production
- Experience with monitoring and observability
- Experience with LLMs
- Experience with agent architectures
- Experience with orchestration frameworks
- Familiarity with synthetic data generation
- Familiarity with evaluation systems
- Familiarity with AI feedback loops
- Experience with agent observability tools
- Experience with ML observability tools
- Experience with model serving
- Experience with model routing
- Experience with inference optimization
- Experience with open-source models
- Experience with custom inference stacks
- Knowledge of system reliability patterns
- Knowledge of failure handling patterns
- Knowledge of safety patterns in AI systems
Aufgaben
- Design and own end-to-end ML and data systems
- Architect scalable data pipelines for RAG, embeddings, and real-time data
- Build and operate production-grade ML services and APIs
- Define standards for infrastructure, deployment, and system reliability
- Integrate ML systems with external APIs and operational platforms
- Lead implementation of security best practices for AI systems
- Ensure secure prompt handling and data privacy
- Protect against adversarial attacks and model injection
- Maintain strict authorization boundaries for AI agents
Berufserfahrung
- ca. 4 - 6 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- SQL
- Docker
- Kubernetes
- Terraform
- LLMs
- LangGraph
- AutoGen
- CrewAI
- Langfuse
- LangSmith
- LLaMA
- Mistral
- Mixtral
Benefits
Mehr Urlaubstage
- 27 days holiday
- Extra holiday day on 2nd year of service
- Extra holiday day on 3rd year of service
Sonstige Zulagen
- 1000 EUR Educational Budget
- Digital meal vouchers
- Food vouchers
Weiterbildungsangebote
- Language courses
- Udemy Business platform access
Familienfreundlichkeit
- Parental support
Gesundheits- & Fitnessangebote
- Health checkups
- Gym subsidy
Mentale Gesundheitsförderung
- Meditation
Firmenfahrrad
- Bicycle subsidy
Attraktive Vergütung
- Employee Share Purchase Plan
Workation & Sabbatical
- Sabbatical bank
Öffi Tickets
- Public transportation ticket discount
Sonstige Vorteile
- Life & accident insurance
Betriebliche Altersvorsorge
- Corporate pension plan
Mitarbeiterrabatte
- Corporate discounts
Über das Unternehmen
Delivery Hero
Branche
IT
Beschreibung
The company is a pioneering local delivery platform operating in over 70 countries, focused on delivering an amazing experience.
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