Delivery Hero

4 weeks ago

Principal ML Engineer (Agentic AI)-Vendor Data Team

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 minutes agoStatus: Live

Job Summary

Hands-on leader designing and shipping end-to-end ML and data systems for an AI-native Vendor Data Team. You’ll build scalable data pipelines (RAG, embeddings, real-time processing), production-grade ML services and APIs, and define infrastructure standards (IaC, containers, orchestration) while integrating with external APIs and ensuring secure, reliable operation.

Location: Berlin

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

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

Pay and Benefits

Perks:Hybrid Work27 DaysEducational BudgetLanguage CoursesHealth InsuranceGym MembershipLife &Corporate PensionMeal VouchersRelocation

Key Requirements

•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

Experience:AIMachine learningData engineering

Skills:Problem-solvingCommunicationTeamwork

Languages:English

Tech Stack:PythonSQLDockerKubernetesCloudTerraform

Company Brief

Delivery Hero

Global online food-ordering and local delivery platform operating multiple regional brands (e.g., Foodpanda, Glovo, Talabat) across 50–70+ countries, supplying food and quick-commerce deliveries via marketplace and logistics services.

Industry: Online Marketplaces

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Berlin, Germany

Founded: 2011

Glassdoor: 3.4

Website LinkedIn Glassdoor

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Delivery Hero

4 weeks ago

Principal ML Engineer (Agentic AI)-Vendor Data Team

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 minutes agoStatus: Live

Job Summary

Location: Berlin

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

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

Pay and Benefits

Perks:Hybrid Work27 DaysEducational BudgetLanguage CoursesHealth InsuranceGym MembershipLife &Corporate PensionMeal VouchersRelocation

Key Requirements

•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

Experience:AIMachine learningData engineering

Skills:Problem-solvingCommunicationTeamwork

Languages:English

Tech Stack:PythonSQLDockerKubernetesCloudTerraform

Company Brief

Delivery Hero

Industry: Online Marketplaces

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Berlin, Germany

Founded: 2011

Glassdoor: 3.4

Website LinkedIn Glassdoor