Senior Machine Learning Engineer - Tech Foundations - Global Machine Learning Platform

Senior Machine Learning Engineer - Tech Foundations - Global Machine Learning Platform

• Full-time

We are on the lookout for a Senior Machine Learning Engineer to join the Tech Foundations - Global Machine Learning Platform team . This role is a premier opportunity to define the architectural future of ML and AI Platforms and drive significant business value across Delivery Hero's diverse brands (Foodora, Foodpanda, Glovo, Talabat, and more).

Your mission is to build and evolve the cutting‑edge, centralized platform that empowers Data Science and Machine Learning Engineering teams to rapidly, reliably, and safely develop, deploy, and manage high‑impact, personalized ML models for millions of customers every day.

Responsibilities

• Architectural Leadership: Define the long‑term technical vision, roadmap, and architecture for components of the Global ML Platform. Lead the design, build, and maintenance of scalable ML infrastructure services (e.g., Model Development, Training, Serving, Monitoring) that manage the entire ML lifecycle at scale.
• System Ownership and Innovation: Drive complex, ambiguous projects end‑to‑end, translating pain points from cross‑functional application teams into robust, high‑impact platform features. Proactively champion and implement new technologies and architectures to support novel use cases.
• Scalability and Resilience: Implement highly available, secure, and performant systems utilizing modern public cloud infrastructure (GCP or equivalent), leveraging Infrastructure as Code (Terraform) and container orchestration (Kubernetes, Helm). Optimize solutions for performance, security, and efficiency on a global scale.
• Mentorship and Standards: Define and enforce engineering best practices (GitOps, Software Design) by writing and sharing comprehensive technical documents and RFCs. Act as a technical mentor, guiding and reviewing the work of junior and mid‑level engineers to ensure code quality, consistency, and team‑wide technical excellence.

Qualifications

• 5+ years of relevant experience in Software Engineering, Machine Learning Engineering, MLOps, or Platform Engineering.
• Proficient in Python or Golang, with a proven ability to write high‑quality maintainable code.
• Extensive experience designing and building complex applications and distributed systems from scratch, applying Software Design, Microservices, and Cloud Architecture Best Practices (GitOps, MLOps, DevOps).
• Mastery of containerization and orchestration tools (Docker, Kubernetes, Helm), CI/CD pipelines, and Infrastructure as Code (Terraform or equivalent).
• Deep familiarity with the end‑to‑end ML engineering ecosystem, including Model Serving, Training, and Feature Engineering pipelines.
• Experience with ML tools such as Metaflow, MLflow, Argo Workflows, Jupyter Notebooks, and Serving Frameworks such as Triton.
• Hands‑on experience with public cloud platforms (GCP, AWS).
• Expert in technical deep‑dives, debugging, and Root Cause Analysis in large‑scale systems.
• Exceptional written and verbal English communication skills, with experience in architectural reviews and cross‑team technical strategy.

Benefits

• 27 days holiday with an extra day on 2nd and 3rd year of service.
• 1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform.
• Health Checkups, Meditation, Yoga, Gym & Bicycle Subsidy.
• Employee Share Purchase Plan, Sabbatical Bank, Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan.
• Digital Meal Vouchers, Food Vouchers, and Corporate Discounts.

Equal Opportunity and Accessibility

We believe diversity and inclusion are key to creating an amazing product and employee experience. We do not discriminate on the basis of race, religion, gender identity, sexual orientation, age, marital or disability status. Please let us know if you need accommodations or accessibility support to ensure a smooth interview experience.

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.