Senior ML Infrastructure / MLOps Engineer (m/w/d)

We are seeking a Senior ML Infrastructure/MLOps Engineer to build and operate a model-serving platform. You will integrate various model frameworks, develop inference APIs, and optimize performance. Responsibilities include containerizing and deploying models with Docker and AWS.

• Build and operate a model-serving platform (e.g., Triton Inference Server)
• Integrate model types and frameworks (PyTorch, TensorFlow)
• Develop inference APIs (batch & streaming)
• Design robust input/output schemas for ML models
• Optimize performance (latency, throughput, GPU utilization)
• Containerize and deploy models (Docker, AWS)

• Excellent Python skills (backend/ML runtime)
• Experience with ML inference & serving (Triton, TorchServe)
• Understanding of model inputs/outputs, batching vs streaming, FP32/FP16/quantization
• Proficiency with Docker and productive deployments
• Strong debugging skills in distributed ML systems
• Basic knowledge of CUDA/GPU computing
• Good German and English language skills