> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt.

# ML Ops DSX Senior Engineer

Canonical URL: https://nextmove.md/fde/jobs/76728b0c4db2d623

NVIDIA posts a senior FDE role to build what the customer runs in Santa Clara, CA +1 · US remote, at $184,000–$356,500 base, above the senior FDE median of $190,000 across 1,864 postings with pay. Build and deploy distributed training, inference, and MLOps solutions on NCP and Neo Cloud platforms. Read from the employer’s posting on November 8, 2026.

- [NVIDIA](https://nextmove.md/fde/companies/nvidia)

First seen Oct 29, 2026 · open on Workday as of Nov 8, 2026

**$184,000–$356,500** *annualized* Santa Clara, CA +1 · US remote Remote

Build and deploy distributed training, inference, and MLOps solutions on NCP and Neo Cloud platforms.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2F76728b0c4db2d623&placement=top)
- [View posting at NVIDIA](https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/ML-Ops-DSX-Senior-Engineer_JR2029008)

Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so.

## At a glance

### Posted base pay

$184K–$357K Above the median

Midpoint $270K · median $190K

This job $184K to $357K. Senior FDE postings, 1,864 postings: the middle 50% of posted pay is $160K to $220K, median $190K.

### The work

Builds what the customer runs

Balance **Mostly building**

Project stages

1. Pre-sales (not covered)
2. Proof of concept (not covered)
3. Implementation
4. Operations

Travel **Required, amount not stated**

- **Coding**: Writes production code

- **Builds for**: External customers

- **Level**: Senior

- **Role**: Technical lead

### What they ask for

Experience

- **8+ years** customer-facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering

Background

- **Software engineering**
- **Solutions and customer engineering**

### Do you meet what the posting states?

The posting asks for 8+ years. How many do you have?

The posting reads as a senior role. What level are you at now?

The work is remote from the US. Can you work from the US?

Which of these have you used in production?

Answer each one. Nothing is saved or sent.

[What postings ask for, by background →](https://nextmove.md/fde/paths)

## Conditions

- **Location**: Santa Clara, CA · Seattle, WA · US remote

- **Work arrangement**: Remote

- **Remote work restrictions**: US

- **Travel**: Travel required, amount not stated

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- [Other jobs at NVIDIA (30)](https://nextmove.md/fde/companies/nvidia)

## The job description from NVIDIA

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.

[View posting at NVIDIA](https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/ML-Ops-DSX-Senior-Engineer_JR2029008)

## About NVIDIA

Full-stack accelerated computing and AI infrastructure company building GPUs, CPUs, networking, systems, software and platforms for data centers, gaming, professional visualization, automotive and robotics.

Public · 5000+ people

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