Build scalable backend systems for distributed AI workloads and federated learning

We're looking for a capable, self-driven Sr. Backend / DevOps Engineer with 5+ years in distributed systems and cloud-native architectures. In this role, you design and scale distributed AI infrastructure, optimize performance across diverse ML workloads, and ensure secure, reliable deployments. You work hands-on on microservices, CI/CD, and multi-cloud environments to support enterprise-scale AI.

Key Responsibilities

Design and Modernize Backend Architecture
Build and Scale Distributed AI Infrastructure
Optimize Performance
Drive MLOps

What we're looking for

5+ years in distributed systems and cloud architecture.

Strong Python/Django with ML integrations
Develop and maintain unit test suites with pytest to ensure code quality
Proficiency with Kubernetes and containerized deployments
Experience with CI/CD pipelines and DevOps practices
Knowledge of database optimization and scaling
Background in building distributed, scalable AI infrastructure
You are a technology generalist and comfortable working in early-stage startups

Nice to have

Federated learning and distributed ML systems
Edge computing
GPU optimization and high-performance computing

What we offer

Impactful Work: Shape how data scientists and AI teams collaborate securely
Growth Opportunities: Work with an experienced leadership team and cutting-edge tech
Competitive Compensation: Upper-market salary, performance incentives, and equity options
Vibrant Culture: Flexible working, diverse team, and creative autonomy in central Berlin

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