Senior Solutions Architect – Large Scale Neural Networks Inference

NVIDIA

Senior Solutions Architect optimizing large-scale neural network inference for NVIDIA’s EMEA AI customers. Architecting production pipelines and shaping the NVIDIA inference technology roadmap.

Posted 9/8/2026full-timeRemote • 🇫🇷 FranceSenior💰 PLN 292,500 - PLN 650,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI inference optimization and production deployment, with a strong focus on high-performance inference pipelines and GPU orchestration. Proven ability to lead technical initiatives and align stakeholders for strategic technology decisions in AI at scale.

Highest-signal resume keywords

AI/ML Infrastructure ExpertiseInference OptimizationNVIDIA Inference Stack ExperienceGPU Orchestration on KubernetesTechnical Leadership

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Applicant Tracking System Keywords

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Hard Skills

LLM/VLM Inference OptimizationTransformer Inference AccelerationQuantization (INT4/FP8)Speculative DecodingContinuous BatchingKV Cache OptimizationWideEP for MoE ModelsGPU Memory HierarchiesLow-Latency NetworkingProduction Deployment at Scale

Soft Skills

Excellent Communication SkillsStakeholder Alignment

Tools & Technologies

NVIDIA DynamoTensorRT-LLMTriton Inference ServerNIMKubernetes

Certifications & Qualifications

MS or PhD in Computer ScienceEngineering

Industry Keywords

AI InferenceHigh-Performance Inference PipelinesInference ChallengesAI Cluster EfficiencyOpen-Source Inference Projects

Tech Stack

Tools & technologies

Kubernetes

About the role

Key responsibilities & impact

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
Improve GPU utilization and AI cluster efficiency
Translate customer insights and deployment patterns into actionable product feedback
Develop the roadmap for the NVIDIA stack, including Dynamo, TensorRT-LLM, and NIM
Define the technical direction for AI inference across EMEA
Align NVIDIA and customer organization stakeholders to influence strategic technology decisions for next-generation AI inference at scale

Requirements

What you’ll need

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 and 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
Experience with NVIDIA's inference stack, including TensorRT-LLM, Triton Inference Server, NIM, and NVIDIA Dynamo
Experience with GPU orchestration on Kubernetes
Experience operating 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

Benefits

Comp & perks

Highly competitive salaries
Comprehensive benefits package