Senior Solutions Architect – Large Scale Neural Networks Inference
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What you'll do
- 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 they're looking for
- 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.
Nice to have
- 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.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer www.nvidiabenefits.com/
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 292,500 PLN - 507,000 PLN for Level 4, and 375,000 PLN - 650,000 PLN for Level 5.


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