NVIDIA’s Worldwide Field Operations (WWFO) team is seeking a Solution Architect with a deep understanding of neural network inference. As our customers adopt increasingly complex inference pipelines on state of the artinfrastructure, there is a growing need for experts who can guide the integration of advanced inference techniques such as speculative decoding, request scheduler optimizations or FP4 quantization. The ideal candidate will be proficient using tools such as TRT LLM, vLLM, SGLang or similar, and have strong systems knowledge, enabling customers to fully use the capabilities of the new GB300 NVL72 systems (for example work on efficient KV cache offloading or help with inference of new architectures like hybrid or diffusion models, or architect the pre- and post-processing pipelines).
Solutions Architects work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence! We need individuals who can enable customer productivity and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for someone always passionate about artificial intelligence, someone who can maintain understanding of a fast paced field, someone able to coordinate efforts between corporate marketing, industry business development and engineering. Solutions Architects, are the first line of technical expertise between NVIDIA and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers in order to promote adoption of NVIDIA based AI technology. Engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a significant part of the Solutions Architect role.
What you will be doing:
Work directly with key customers to understand their technology and provide the best AI solutions.
Perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems (in particular Grace/ARM based systems). This includes support in optimization of large scale inference pipelines.
Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations.
What we need to see:
Excellent verbal, written communication, and technical presentation skills in English.
MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields.
5+ years work or research experience with Python/ C++ / other software development
Work experience and knowledge of modern NLP including good understanding of transformer, state space, diffusion, MOE model architectures. This can include either expertise in training or optimization/compression/operation of DNNs.
Understanding of key libraries used for NLP/LLM training (such as Megatron-LM, NeMo, DeepSpeed etc.) and/or deployment (e.g. TensorRT-LLM, vLLM, Triton Inference Server).
Enthusiastic about collaborating with various teams and departments—such as Engineering, Product, Sales, and Marketing—this person thrives in dynamic environments and stays focused amid constant change.
Self-starter with demeanor for growth, passion for continuous learning and sharing findings across the team.
Ways to Stand Out from The Crowd:
Demonstrated experience in running and debugging large-scale distributed deep learning training or inference processes.
Experience working with larger transformer-based architectures for NLP, CV, ASR or other.
Applied NLP technology in production environments.
Proficient with DevOps tools including Docker, Kubernetes, and Singularity.
Understanding of HPC systems: data center design, high speed interconnect InfiniBand, Cluster Storage and Scheduling related design and/or management experience.
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 to you and your family 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.
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NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
