Role Overview
We are looking for a Senior Solutions Architect with deep experience in large-scale production AI inference. You will collaborate with top EMEA AI Natives, AI infrastructure providers, and enterprises deploying AI at scale. As a trusted technical leader, you will ensure NVIDIA's inference stack achieves best performance, efficiency, and reliability. You will address the industry's toughest AI inference challenges at the intersection of AI and high-performance computing, driving innovations in areas such as multi-node Mixture-of-Experts (MoE) serving, interconnect-aware scheduling, memory-bound workload optimization, and next-generation inference architectures. Your work will establish the technical direction for scalable, high-performance AI inference across the most demanding production environments.
Responsibilities
- Guide EMEA AI Natives customers in deploying and optimizing large-scale inference workloads on multi-node GPU clusters.
- Architect efficient inference pipelines for dense and sparse/latent MoE models distributing workload among thousands of GPUs.
- Improve inference efficiency across quantization (INT4/FP8), speculative decoding, disaggregated prefill/decode, KV cache management, and WideEP for large MoE deployments.
- Collaborate with NVIDIA product teams (Dynamo, TensorRT-LLM, NIXL) to accelerate customer success.
- Animate the AI inference developer’s community across EMEA through technical workshops, hackathons, and reference architectures.
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/. For Poland: The base salary range is 292,500 PLN - 507,000 PLN.
Required Qualifications
- MS or PhD in Computer Science, Engineering, High-Performance Computing, or equivalent professional experience.
- 5+ years of experience in Neural Networks inference optimization.
- Solid understanding of transformers inference optimization: quantization, disaggregated inference, speculative decoding, continuous batching, KV cache optimization.
- Practical experience in MoE inference at scale: expert parallelism, WideEP, all-to-all communication, routing overhead, and load balancing at scale.
- Ability to engage effectively with ML engineers, researchers, and systems architects at a deep technical level.
Preferred Skills
- Hands-on experience with NVIDIA Dynamo, NIXL, Grove, or emerging disaggregated inference tooling.
- Understanding of GPU memory hierarchies and high-speed interconnects (NVLink, InfiniBand, RDMA, UCX).
- You have contributed to advanced AI lab or large scale AI infrastructure providers performing inference on thousands of GPUs.
- Published work or benchmarks in large-scale AI inference.
