AI Inference Platform Engineer in Berlin

• AI Infrastructure | Model Serving | GPU Computing | Inference Engineering | ML Platforms
• Our client, a growing
• AI Infrastructure company based in Berlin, is looking for an

AI Inference Platform Engineer to build and optimise the platform used to serve production AI models across GPU-enabled infrastructure.

You'll work at the intersection of

AI Infrastructure, Distributed Systems, and Platform Engineering , focusing on inference performance, GPU utilisation, autoscaling, latency, and reliability.

• What You’ll Work On
• Build and operate Kubernetes infrastructure for production AI inference
• Deploy and optimise model-serving workloads using v LLM and NVIDIA Triton
• Improve GPU utilisation, throughput, and inference latency
• Design autoscaling strategies for dynamic AI workloads
• Build platform tooling and automation in Python
• Provision and manage infrastructure using Terraform
• Develop observability across models, GPUs, Kubernetes, and serving infrastructure
• Profile and troubleshoot inference performance bottlenecks
• Improve batching, concurrency, caching, and resource allocation strategies
• Build reliable deployment workflows for new models and model versions
• Partner with ML Engineers to move models efficiently into production
• Core Skills
• 4+ years in AI Infrastructure, ML Infrastructure, MLOps, Platform Engineering, or similar roles
• Strong understanding of Linux and distributed production systems
• Nice to Have
• CUDA
• NVIDIA GPU Operator
• Py Torch
• KServe
• Ray Serve
• LLM inference optimisation
• Multi-GPU inference
• AWS / GCP GPU infrastructure
• Experience operating high-throughput or latency-sensitive inference services
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