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NCX Senior Engineer

NVIDIA· Engineer, Sys SW
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US, CA, Santa Clara, US, WA, Seattle, Remote$184k - $287.5kFull-timePosted 3mo ago

About the role

NVIDIA seeks an NCX Senior Engineer to join the DSX team, collaborating with strategic customers to implement and enhance AI workloads, deliver hands-on technical assistance for advanced AI deployments, and ensure customers realize efficient performance from NVIDIA's AI platform across environments.

Responsibilities

  • Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines on NVIDIA reference architectures.
  • Act as the main technical contact for strategic NCPs, offer remote and on-site support, troubleshoot complex production problems, and guide partner engineering teams on NVIDIA platform guidelines.
  • Deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems aligned to NCP builds.
  • Profile and tune large-scale training and inference workloads on NCP platforms. Implement observability and SLO/SLA monitoring. Lead efforts to reduce latency, cost, and operational risk.
  • Implement and expand NVIDIA reference architectures on partner platforms, develop integrations with partner control planes and customer environments, and ensure smooth API, data pipeline, and enterprise software connectivity.
  • Build detailed implementation guides, runbooks, and post-mortem documentation that codify standard methodologies for running NVIDIA AI workloads at scale on NCP platforms.

Qualifications

  • BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or related field, or equivalent experience.
  • 8+ years in customer-facing technical roles (Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering), ideally in large-scale cloud or service provider environments.
  • Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant/service-provider platforms.
  • Demonstrated AI/ML experience supporting large-scale training and inference workloads (LLMs, generative models, recommendation systems) in production.
  • Solid programming skills in Python/Go, with hands-on experience using PyTorch or TensorFlow for training and serving.
  • Ability to collaborate with customer and partner engineering teams, guide investigations, and drive root-cause resolution.
  • Excellent communication and technical presentation skills for architectures, trade-offs, and recommendations.

Skills

Required:LinuxKubernetescontainersGPU schedulingPython/GoPyTorch / TensorFlowAI/ML workloads

Benefits

  • equity
  • benefits (as per company benefits)
Last updated Sep 4, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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