Senior Solutions Architect – Large Scale Neural Networks Inference

We are seeking a Senior Solutions Architect with deep expertise in large-scale neural network inference and a proven ability to lead technical collaboration with frontier AI labs and enterprises deploying AI at scale across EMEA. In this role, you will define the technical direction for AI inference across EMEA by identifying critical bottlenecks and driving the development of scalable, high-impact solutions. By aligning key team members within NVIDIA and customer organizations, you will influence strategic technology decisions to develop the deployment of next-generation AI inference at scale.

What you will be doing:

• Lead the inference strategy for a portfolio of EMEA AI Natives customers, guiding engagements from initial proof of concept to production-scale deployments.
• Identify inference challenges across customer deployments including latency, efficiency, cost per token, memory utilization, and low-latency networking.
• Architect and optimize high-performance inference pipelines using NVIDIA Dynamo, TensorRT-LLM, vLLM, SGLang, and other inference backends, improving GPU utilization and AI cluster efficiency.
• Translate customer insights and deployment patterns into actionable product feedback that develops the roadmap for NVIDIA stack such as Dynamo, TensorRT-LLM, and NIM.

What we need to see:

• MS or PhD in Computer Science, Engineering, or equivalent experience in the field.
• 8+ years in AI/ML infrastructure, with deep expertise in LLM/VLM inference optimization and production deployment at scale.
• Deep understanding of transformer inference acceleration: quantization (INT4/FP8), speculative decoding, disaggregated inference, continuous batching, KV cache optimization, and WideEP for MoE models.
• Understanding of GPU memory hierarchies and low-latency networking along with their influence on inference performance.
• Proven track record to lead technical initiatives.
• Excellent communication skills, effective with research scientists, infrastructure engineers, and executive team members.

Ways to stand out from the crowd:

• Experience with NVIDIA's inference stack, including TensorRT-LLM, Triton Inference Server, NIM, and NVIDIA Dynamo.
• Experience with GPU orchestration on Kubernetes.
• You have operated inference at scale inside a frontier AI lab or hyperscale's inference team.
• Contributions to open-source inference projects such as vLLM, SGLang, KServe, or NVIDIA Dynamo.