Senior Production Engineer, Object Store

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $176,000–$276,000 / yr
Employment: Full-time
Posted: 3 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 $196k

This role $226k

$142k $290k

below market most similar roles pay here above market

This role pays more than 72% of similar roles. Most pay $159,750–$231,487 — the blue band above. At the midpoint, this role pays about $226k versus about $196k 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 Production Engineer, Object Store

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The Senior Production Engineer, Object Store - DGX Cloud joins the team responsible for the storage platform serving AI/ML datasets, checkpoints, and artifacts for GPU workloads. You will operate large object storage deployments end to end, managing API and metadata tiers, data placement, replication, erasure coding, and security. Daily responsibilities include automating fleet lifecycles, provisioning bare-metal hardware, forecasting capacity, and shipping storage software through CI/CD pipelines. You will define SLOs for availability and latency while ensuring 24/7 operational excellence. Required skills include deep knowledge of object storage internals, S3 API semantics, and Linux performance analysis. You must be proficient in Python, shell, Ansible, Kubernetes, Git, Prometheus, and Grafana to manage petabyte-scale infrastructure and solve complex hardware faults across the storage stack.

Skills

Object Storage Python Ansible Kubernetes CI/CD Infrastructure as Code Prometheus Grafana Linux S3 API Shell Git Erasure Coding Bare Metal Networking SLOs

What you'll do

Operate large object storage deployments end to end, including metadata tiers, data placement, replication, and erasure coding.
Define SLOs for availability, latency, and durability while managing error budgets with platform teams.
Automate the fleet lifecycle, including bare-metal provisioning, drive onboarding, rebalancing, and firmware updates.
Bring new data halls and regions into production involving hundreds of petabytes of data.
Ship storage software and configurations using CI/CD, Ansible, Kubernetes, and canary rollouts.
Forecast capacity with supply chain teams and tune performance for AI access patterns.
Provide 24/7 operational support, including global on-call rotations and writing blameless postmortems.

What we're looking for

BS degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
8+ years in SRE, production engineering, or infrastructure operations.
3+ years running distributed object storage in production at petabyte scale or larger.
Deep knowledge of object storage internals, including data placement, replication, erasure coding, consistency, failure domains, and S3 API semantics.
Strong Linux skills on bare metal across storage, networking, and performance analysis.
Proficiency in Python and shell for automation, plus hands-on experience with Ansible, Git workflows, and CI/CD.
Experience building observability with Prometheus and Grafana, defining SLOs, and writing postmortems, runbooks, and design docs.
Experience operating object storage at petabyte-to-exabyte scale, migrating petabytes between clusters, or serving AI/ML data pipelines (preferred).

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