NCX Senior Engineer

NVIDIA
United States
Workplace: HybridFull timeUSD 184,000 - 356,500 annuallyFunction: Solutions Engineering & Sales EngineeringExperience: 8+ yearsEducation: bachelorsSkills: ["Communication","Technical presentation","Collaboration","Problem-solving","Troubleshooting"]

Collaborate with strategic customers to implement and enhance large-scale AI workloads on NVIDIA’s NCP and Neo Cloud platforms. Build and deploy distributed training and inference solutions, deploy/manage workloads across DGX Cloud and data centers, and tune performance using observability and SLO/SLA monitoring. Act as a technical contact for remote and on-site support, guide partners on NVIDIA platform guidelines, and produce runbooks and implementation documentation.

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FursaFursa
NVIDIA
NVIDIA
1 month ago

NCX Senior Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Collaborate with strategic customers to implement and enhance large-scale AI workloads on NVIDIA’s NCP and Neo Cloud platforms. Build and deploy distributed training and inference solutions, deploy/manage workloads across DGX Cloud and data centers, and tune performance using observability and SLO/SLA monitoring. Act as a technical contact for remote and on-site support, guide partners on NVIDIA platform guidelines, and produce runbooks and implementation documentation.
Location: United States
Workplace: Hybrid
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Build and deploy custom AI solutions on NCP and Neo Cloud, including distributed training, inference optimization, and MLOps pipelines using NVIDIA reference architectures.
  • •Serve as the main technical contact for strategic NCPs, providing remote and on-site support, troubleshooting complex production issues, and guiding partner engineering 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 aligned to NCP builds.
  • •Profile and tune large-scale training and inference workloads; implement observability and SLO/SLA monitoring; work to reduce latency, cost, and operational risk.
  • •Implement and expand NVIDIA reference architectures on partner platforms, develop integrations for control planes and customer environments, and create implementation guides and runbooks.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually
Equity and Bonus:Equity

Key Requirements

  • •BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
  • •8+ years in customer-facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally for large-scale cloud or service provider environments.
  • •Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant or service-provider platforms.
  • •Demonstrated AI/ML production experience supporting large-scale training and inference (e.g., LLMs, generative models, recommendation systems).
  • •Solid programming skills in Python/Go, with hands-on experience using PyTorch or TensorFlow for training and serving.
Experience:8+ yearsAIMLMLOpsCloudService providerLLMsGenerative modelsRecommendation systems
Education:Bachelor's in Computer Science; Computer/Electrical Engineering; or related technical field
Skills:CommunicationTechnical presentationCollaborationProblem-solvingTroubleshooting
Tech Stack:NCPNeo CloudDGX CloudKubernetesContainersGPU schedulingLinuxDistributed computingCUDANeMoTritonNIMInfiniBandRoCEMLOpsCI/CDPrometheusGrafanaOpenTelemetryGitOps

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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