
Leading supplier of end-to-end high speed Ethernet and InfiniBand intelligent interconnect solutions and services.

Leading supplier of end-to-end high speed Ethernet and InfiniBand intelligent interconnect solutions and services.
Company: NVIDIA
Core focus: Accelerated computing and AI infrastructure (GPUs, data center and AI systems, edge/robotics, automotive)
Founded: April 1993
Public company / Investor relations: Maintains an active investor relations portal with quarterly results and presentations
High-performance graphics, machine learning/AI acceleration, and full-stack AI infrastructure for enterprise, cloud and edge use cases.
1993
Semiconductors / AI infrastructure
Historical financing and IPO-related information are documented on financial profiles; NVIDIA also deploys strategic investments in startups (examples reported)
$2B
Reported $2B investment to support CoreWeave's AI compute expansion
We’re forming a team of innovators to roll out and enhance AI inference solutions at scale, demonstrating NVIDIA’s GPU technology and Kubernetes. As a Solutions Architect (Inference Focus), you’ll collaborate closely with our engineering, DevOps, and customer success teams to foster enterprise AI adoption. Together, we'll introduce generative AI to production! What you'll be doing: - Help customers craft, deploy, and maintain scalable, GPU-accelerated inference pipelines on Kubernetes for large language models (LLMs) and generative AI workloads. - Enhance performance tuning using TensorRT/TensorRT-LLM, NVIDIA NIM, and Triton Inference Server to improve GPU utilization and model efficiency. - Collaborate with multi-functional teams (engineering, product) and offer technical mentorship to customers implementing AI at scale. - Architect zero-downtime deployments, autoscaling (e.g., HPA or equivalent experience with custom metrics), and integration with cloud-native tools (e.g., OpenTelemetry, Prometheus, Grafana). What we need to see: - 5+ Years in Solutions Architecture with a proven track record of moving AI inference from POC to production on Kubernetes. - Experience architecting GPU allocation using NVIDIA GPU Operator and NVIDIA NIM Operator. Troubleshoot sophisticated GPU orchestration, optimize with Multi-Instance GPU (MIG), and ensure efficient utilization in Kubernetes environments. - Proficiency with TensorRT-LLM, Triton, and TensorRT for model optimization and serving. - Success stories optimizing LLMs for low-latency inference in enterprise environments. - BS or equivalent experience in CS/Engineering. Ways to stand out from the crowd: - Prior experience deploying NVIDIA NIM microservices for multi-model inference. - Serverless Inference, knowledge of FaaS patterns (e.g., Google Cloud Run, AWS Lambda, NVCF) with NVIDIA GPUs. - NVIDIA Certified AI Engineer or similar. - Active contributions to Kubernetes SIGs or AI inference projects (e.g., KServe, Dynamo, SGLang or similar). - Familiarity with networking concepts which support multi-node inference such as MPI, LWS or similar. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 8, 2025.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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