Description
We are seeking an experienced Solutions Architect to be a trusted technical advisor, bridging design to deployment of large-scale AI/HPC GPU infrastructure. You will collaborate with NVIDIA Cloud Partners to create, implement, and deliver on NVIDIA's innovative hardware and software solutions.
Your responsibilities will include partnering with SAs, Account Managers, Engineering, Product, and business leaders to align on strategies, assess technical needs, secure business opportunities for NVIDIA. You will become the primary technical driver for customers during the design, development, construction, integration, and production of GPU Cloud infrastructure and applications throughout the entire customer lifecycle.
You will conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions. You will work closely with customers to build and adopt NVIDIA solutions including PoCs to address critical business needs covering infrastructure, libraries, and applications.
You will prepare and deliver technical content to customers including presentations, workshops, reference architectures, tutorials, publications.
We are looking for a candidate with a BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or other Engineering fields or equivalent experience. You should have 10+ years of Solution Engineering (or similar Sales Engineering, Cloud Engineering, Solution Architecture) including experience working directly with partners and customers.
You should have experience crafting and deploying large-scale cluster environments, hands-on experience designing, developing, delivering distributed Cloud architectures. You should have strong fundamentals in programming, optimizations and software design, especially in Python and Deep Learning frameworks such as PyTorch and TensorFlow.
You should have practical expertise fine-tuning and deploying models, integrating software application stacks, libraries, and frameworks to drive consumption from GPU platforms. You should be motivated and skilled to own and drive complex multi-disciplinary technical engagements with customers throughout the full customer lifecycle and cross-functional teams.
You should have efficient time management and capable of balancing multiple tasks. Excellent presentation, communication and collaboration skills are required.
Preferred qualifications include practical experience with NVIDIA GPUs, software libraries, frameworks, and foundation models, such as NVIDIA Nemotron, NVIDIA NeMo Framework, NVIDIA Dynamo, NeMo Retriever, NVIDIA Triton Inference Server, TensorRT, TensorRT-LLM, NVIDIA CUDA-X.
You should have hands-on expertise with scaled AI cloud environments (e.g., AWS, Azure, GCP) and on-premises/hybrid infrastructure, in particular inference and training workloads.
Familiarity with NVIDIA hardware (such as GPUs, networking, storage) and systems technology such as NCCL, DCGM, UFM, Mission Control, Base Command Manager is preferred.
Proficiency with large-scale AI model training/deployment encompassing GPU systems, performance testing, AI benchmarking, fine-tuning, strong focus on MLOps and cluster orchestration (SLURM, K8s, orchestrator, load balancing, cloud architecture) is desired.
Experience working with enterprise developers and strong customer-facing skills are required.