Senior Customer Success Engineer

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $200,000–$322,000 / yr
Employment: Full-time
Posted: 78 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $193k

This role $261k

$132k $342k

below market most similar roles pay here above market

This role pays more than 91% of similar roles. Most pay $153,870–$231,150 — the blue band above. At the midpoint, this role pays about $261k versus about $193k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Customer Success Engineer

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JOB TITLE: Senior Customer Success Engineer - DGX Cloud The Senior Customer Success Engineer - DGX Cloud joins the DGX Cloud organization to bridge customer success and cloud infrastructure engineering. You will partner with internal research and product teams to understand specific workloads, translating that knowledge into architectural guidance, best practices, and hands-on solutions. Your daily responsibilities include designing and implementing distributed cloud infrastructure across compute, storage, networking, and GPU capacity management for IaaS, PaaS, and SaaS models. You will write production code, build agentic tooling to automate operational workflows, and codify working patterns into reusable playbooks. Required skills include experience with Golang, Java, C, C++, Python, or Rust, along with Kubernetes, distributed task scheduling, and DevOps scripting. You will solve complex infrastructure efficiency problems for high-performance computing and AI/ML workloads.

Skills

Golang Java C C++ Python Rust Kubernetes Distributed Systems Cloud Infrastructure IaaS PaaS SaaS DevOps Networking Storage AI/ML GPU Capacity Management High-Performance Computing Zendesk

What you'll do

Design and implement distributed cloud infrastructure for compute, storage, networking, and GPU capacity management.
Provide architectural guidance to internal research and product teams to optimize their specific AI workloads.
Write production code to advance projects and codify working patterns into reusable tools and playbooks.
Build and maintain agentic tooling to automate operational workflows and infrastructure resource management.
Analyze ecosystem demand to drive infrastructure efficiency initiatives in partnership with Engineering, Finance, and Product.
Present technical roadmaps and architecture decisions to internal stakeholders and NVIDIA leadership to drive consensus.

What we're looking for

BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.
12+ years of experience designing and building distributed systems and cloud infrastructure.
Demonstrated experience in GPU capacity management for high-performance computing.
Demonstrated ability to write production code in Golang, Java, C, C++, Python, or Rust.
Experience with Kubernetes and/or distributed task scheduling.
Strong background in Infrastructure, Networking, Storage, and DevOps scripting/tooling.
Experience deploying AI/ML workloads at scale.
Strong communication and relationship-building skills to drive cross-functional consensus and align stakeholders.

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