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ML Ops DSX Senior Engineer

NVIDIA

Santa Clara, CAFull-time$184–357K/yrPosted 2 days agoStill listed today

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At a glance

Compensation
$184–357K/yr
Location
Santa Clara, CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

NVIDIA seeks a Senior Engineer for its DSX team to help strategic customers implement and enhance AI workloads. The role provides hands-on technical assistance for AI deployments and distributed systems, develops solutions across NVIDIA and partner platforms, and supports performance and operational improvements. The engineer will collaborate with customer and partner teams across cloud and service-provider environments.

Skills & qualifications

RequiredNice to have

Skills

Linux SystemsDistributed ComputingKubernetesContainersGPU SchedulingAI/ML WorkloadsLarge-Scale TrainingInference WorkloadsPythonGoPyTorchTensorFlowCustomer CollaborationTechnical InvestigationsRoot Cause AnalysisCommunicationTechnical PresentationsDGX SystemsCUDANeMoTritonNIMInfiniBandRoCEMLOpsCI/CDObservabilityPrometheusGrafanaOpenTelemetryGitOpsInfrastructure as CodeTerraformAnsible

Qualifications

Bachelor's, Master's, PhD or Equivalent8+ Years Customer-Facing Technical Experience

Full job description

NVIDIA is seeking an NCX Senior Engineer to join our DSX team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads! You will deliver hands-on technical assistance for advanced AI deployments, intricate distributed systems, and ensure customers realize efficient performance from NVIDIA's AI platform across varied environments. We partner with the world's most innovative AI companies to address their most challenging technical problems.

What you will be doing: In this role, you will develop innovative solutions that advance AI infrastructure capabilities. You will directly influence customer success with breakthrough AI initiatives.

  • Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines constructed 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 detailed 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.

What we need to see:

  • BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
  • 8+ years of experience in customer facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally supporting 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 experience supporting large‑scale training and inference workloads (e.g., LLMs, generative models, recommendation systems) in production or critically important environments.
  • Solid programming skills in Python/Go, with hands‑on experience using frameworks such as PyTorch or TensorFlow for training and serving.
  • Demonstrated capability to collaborate with customer and partner engineering teams in fast-paced environments, guide intricate technical investigations, and bring issues to root cause and resolution.
  • Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade‑offs, and recommendations to both engineering and leadership audiences.

Ways to stand out from the crowd:

  • Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, Triton, NIM, and NVIDIA networking technologies such as InfiniBand and RoCE.
  • Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms, including implementation of NVIDIA reference architectures for AI infrastructure.
  • Deep familiarity with MLOps and cloud‑native practices: containerization, CI/CD pipelines, observability stacks (Prometheus, Grafana, OpenTelemetry), and GitOps workflows.
  • Background in infrastructure as code (Terraform, Ansible, or similar) for repeatable deployment and configuration of GPU‑accelerated clusters and NCP building blocks.

NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world’s most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 1, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

How this job compares

Set against the 1,436 open Solutions Engineer jobs on Olive Jobs, counted October 29, 2026.

Pay
  • This posting$184–357K/yr
  • California median$152–225K/yr281 salary ranges
  • US median$139–215K/yr1,097 salary ranges

This range's midpoint, $270K, is 42% above the California median midpoint ($190K) — in the top quarter of Solutions Engineer salary ranges in California.

Openings
Olive Jobs lists 356 open Solutions Engineer jobs in California and 1,436 across the US. 24% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 8 years of experience — more than three in four Solutions Engineer postings that state a minimum ask for (median 5 years, across 1,187 postings).
Education
285 of the 1,436 open Solutions Engineer jobs (20%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on October 29, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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