# NCX Senior Engineer

**Company**: NVIDIA
**Location**: Santa Clara, CA
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/NCX-Senior-Engineer_JR2021935-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_246325b0-919

## Description

NVIDIA is seeking an NCX Senior Engineer to join our AI Accelerator 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.

**Responsibilities:**

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.

**Requirements:**

- 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.

**Nice to Have:**

- 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.

## Skills

### Required
- Linux systems
- distributed computing
- Kubernetes
- containers
- GPU scheduling
- Python
- Go
- PyTorch
- TensorFlow
- AI/ML
- MLOps

### Nice to have
- NVIDIA ecosystem
- DGX systems
- CUDA
- NeMo
- Triton
- NIM
- InfiniBand
- RoCE
- cloud-native practices
- containerization
- CI/CD pipelines
- observability stacks
- GitOps workflows
- infrastructure as code
- Terraform
- Ansible

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/NCX-Senior-Engineer_JR2021935-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)