Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building and scaling an AI agent platform for last-mile delivery optimization with an accent on LLM-powered agents, RAG pipelines, and production reliability. Focus on designing scalable AI infrastructure, implementing evaluation frameworks, and optimizing agentic workflows for global operations.

Location: Hybrid (Berlin, Germany). Must be based in or be able to relocate to Berlin, Germany (attendance at the Berlin campus 2 days a week).

Company

A pioneering local delivery platform operating in over 70 countries, focusing on efficient, affordable, and sustainable last-mile delivery.

What you will do

• Build and scale AI agents capable of reasoning, tool calling, and interacting with internal services and data systems.
• Develop and maintain Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic retrieval systems.
• Design and implement evaluation frameworks and safety guardrails for agent behavior and model performance.
• Implement observability, monitoring, and cost visibility for LLM and agent workloads.
• Collaborate with data scientists and platform engineers to integrate AI systems with the broader ML ecosystem.
• Optimize systems for performance, reliability, and cost efficiency while operating AI workloads at scale.

Requirements

• Proven experience shipping LLM-powered systems or AI agents into production.
• 4+ years of experience in production machine learning infrastructure, specifically involving LLMs.
• Strong programming skills in Python with experience building scalable backend services.
• Experience with Cloud platforms, ideally AWS or GCP.
• Strong communication skills and ability to work collaboratively in cross-functional teams.

Nice to have

• Experience with Kubernetes, Terraform, Kafka, MLflow, or Kubeflow.
• Experience with LLM application frameworks such as LangChain, LangGraph, or LlamaIndex.
• Experience with ML frameworks such as Hugging Face or PyTorch.

Culture & Benefits

• Hybrid working model with 2 days a week in the Berlin campus.
• 27 days of holiday, increasing with years of service.
• €1,000 Educational Budget, language courses, and access to Udemy Business.
• Health checkups, meditation, and gym/bicycle subsidies.
• Employee Share Purchase Plan, corporate pension plan, and life/accident insurance.
• Relocation support and dedicated relocation hub for moving to Berlin.