running both ML/LLM workloads and general applications

• Deploy and optimize LLM inference systems
• Design, build, and improve MLOps/DevOps pipelines to support the entire development lifecycle
• Manage GPU scheduling and autoscaling with Kubernetes-native tooling
• Ensure observability and alerting across the platform
• Operate and troubleshoot supporting infrastructure
• Contribute to platform reliability, security, and performance through automation and best practices

Requirements

• 5+ years of experience in MLOps or SRE
• Strong hands-on Kubernetes experience, including GitOps (Flux or ArgoCD), Kustomize, Helm and production troubleshooting
• Familiarity with LLM inference deployment and optimization in Kubernetes (e.g., vLLM, LMCache, llm-d)
• Experience with MLOps supporting tools such as MLflow or Argo Workflows
• Understanding of GPU resource orchestration in Kubernetes environments
• Profound knowledge of observability tools, such as VictoriaMetrics, VictoriaLogs and Grafana
• Knowledge of database and broker administration (PostgreSQL, Redis and RabbitMQ)
• Solid scripting skills in Python
• Comfortable working with cloud platforms (OVHcloud, AWS, GCP or Azure)

Nice-to-Haves

• Experience with audio ML models or real-time inference
• Exposure to CI/CD practices tailored for ML systems
• Familiarity with Kubernetes networking, security, or performance tuning

Benefits

• Full ownership of a mission-critical platform
• A team that values curiosity, learning, and experimentation
• Remote-first setup with the option to work in our Berlin office
• Competitive salary depending on experience
• Work on AI infrastructure that directly impacts healthcare innovation

If you're passionate about web development and want to work with cutting-edge technologies, we'd love to hear from you!

I'm Margarita and will be guiding you through the application process.