Senior Production Engineer

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $184,000–$287,500 / yr
Employment: Full-time
Posted: 2 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 $188k

This role $236k

$128k most similar roles pay here $305k

This role pays more than 84% of similar roles. Most pay $151,900–$223,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $188k 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 1391 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1116 roles with salary data.

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At a glance

TL;DR · Senior Production Engineer

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Senior Production Engineer - DGX Cloud As a Senior Production Engineer on the Production Engineering team, you will build and operate production software, automation, and tooling to ensure reliable, scalable, and safe services for inference and agentic workloads. You will manage control plane services, model deployments, and infrastructure across Kubernetes clusters in multi-cloud and on-premises environments. Your daily work involves improving endpoint availability, capacity management, and service health through GitOps, infrastructure as code, and automated workflows to replace manual tasks. You will define SLIs and SLOs while participating in incident response to troubleshoot failures across routing and model runtimes. Required skills include Python or Go programming, Linux, Kubernetes, and networking fundamentals. Experience with vLLM, SGLang, PyTorch, TensorRT-LLM, CUDA, Terraform, and Argo CD is highly valued for managing large-scale distributed systems and complex AI inference platforms.

Skills

Kubernetes Python Go Terraform Argo CD vLLM SGLang PyTorch TensorRT-LLM NVIDIA Dynamo CUDA NCCL GitOps CI/CD Linux Distributed Systems Infrastructure as Code

What you'll do

Build and operate production software, automation, and tooling for control plane services and model deployments.
Improve the reliability of inference platforms through health validation, safer rollouts, and observability.
Manage endpoint availability, inference routing, and capacity to maintain performance during fluctuating demand.
Deploy and configure services across multi-cloud environments using infrastructure as code and GitOps.
Automate manual workflows for service enablement, model releases, and deprecation processes.
Define and instrument SLIs and SLOs to monitor system health and guide reliability improvements.
Participate in on-call rotations and troubleshoot failures across routing, runtimes, and hardware.
Develop durable fixes and automation to resolve recurring production issues.

What we're looking for

8+ years of experience building or operating production services and large-scale distributed systems with hands-on automation.
Strong programming skills in Python, Go, or a comparable language for developing production tools.
Experience with infrastructure as code, configuration management, or GitOps to automate service deployments.
Strong knowledge of Linux, Kubernetes, containers, cloud infrastructure, distributed systems, and networking fundamentals.
Understanding of SRE principles including SLIs, SLOs, error budgets, incident response, and reducing operational toil.
Experience instrumenting services using metrics, logs, and traces to improve system reliability.
BS/MS in Computer Science or equivalent experience.
Familiarity with vLLM, SGLang, PyTorch, TensorRT-LLM, NVIDIA Dynamo, CUDA, or NCCL (preferred).