Solution Architect - Jr/Mid Level (Hybrid)

A fantastic opportunity for an experienced Solution Architect to join a Global Tech Company, alongside their team in Munich, Germany.

Key requirements:

• Previous experience in a technical partner pre-sales or consulting role with a heavy emphasis on partner and customer-facing interactions (i.e. Solutions Architect, Sales Engineer, Implementation Consultant)
• Excellent communication and presentation skills, able to interface effectively with technical and non-technical stakeholders; experience writing technical proposals or responding to RFPs/tenders; experience running hands-on product demos independently.
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, AzureML), including sovereign, on-premise, and hybrid deployment models.
• Familiarity with MLOps tools and practices: CI/CD, monitoring, and orchestration frameworks (e.g., Kubeflow, Flyte, MLflow); proficiency with Docker and Kubernetes for AI workload containerization.
• Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model delivery formats (ONNX, .safetensors, HuggingFace model hub).
• Experience sizing GPU infrastructure for LLM inference or training workloads (memory, throughput, hardware tiers from A10 to H200).
• Experience benchmarking and evaluating LLM performance (accuracy, latency, throughput).
• Hands-on coding skills in Python, SQL, and familiarity with ML libraries and frameworks (PyTorch, TensorFlow, Hugging Face).
• Bachelor's or master's degree in Computer Science, Data Science, Engineering, or related field.
• Must be available to travel as needed for meetings, conferences, and project requirements.

Preferred Qualifications:

• Experience with Computer Vision models, Speech models, Vision-Language models, and other modalities.
• Experience with AI model optimization, quantization, or deployment to edge devices.
• Experience designing data architectures (batch & streaming) and working with big data technologies.
• Knowledge of data privacy and ethical considerations in AI, including GDPR compliance and familiarity with the EU AI Act

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