Manager, Software Engineering
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2d ago
The date the source published, not the day we noticed it (2026-11-04). Last seen at its source 3h ago.
We have tracked this listing since 4 Nov 2026 (1 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.
Is it remote?
US, CO, Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$224k–356.5k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workday employer's own board first seen 1d ago · last seen 3h ago
The listing
NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Research Superclusters (MARS), builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you'll help build solutions that power some of the most sophisticated computing workloads globally.
We build and run the platform that NVIDIA's own researchers use to train frontier models. That means some of the largest GPU clusters in the world, spread across multiple clouds and partners, used for pre-training, post-training and reinforcement learning. Our engineers own how work gets scheduled onto that fleet, how data and checkpoints move through it, and the Kubernetes-based platform underneath. We are looking for an engineering manager to lead one of these engineering teams. You will grow a team of strong engineers, own a platform area end to end, and work directly with research teams whose results depend on it. You will shape what the platform becomes, not only keep it running.
What you'll be doing:
- Lead, hire and grow a team of software and systems engineers, including senior and staff-level engineers and tech leads.
- Lead a core part of the AI infrastructure platform end to end: its roadmap, architecture, reliability and on-call health.
- Turn research needs into platform capabilities by working directly with model training teams.
- Set clear ownership and decision rights for your area: named owners, written decisions, and clean interfaces to partner teams.
- Drive engineering quality at fleet scale: automation over manual operations, observability built in, safe rollouts across many clusters.
- Partner with infrastructure, storage, networking, Kubernetes and cloud-provider teams across NVIDIA, and with external vendors and open-source communities.
- Measure what matters for researchers, such as reliability, latency, and use it to set priorities.
- Contribute to the shared Kubernetes-based platform codebase, including its open-source path, alongside your own team's systems.
What we need to see:
- BS or MS in Computer Science, Computer Engineering or a related field, or equivalent experience.
- 12+ overall years in software engineering, with 5+ years managing engineering teams, including leading tech leads or managers.
- A track record of building and running large-scale distributed systems in production: clusters, platforms or infrastructure services used by other engineers.
- Hands-on depth in at least one of: workload scheduling and resource management, distributed storage and data systems, or Kubernetes-based platforms.
- Hiring and growing senior engineers, and building teams that keep quality high under pressure.
- Experience owning reliability for critical services: on-call, incident response, postmortems and the fixes that follow.
- Clear written communication. You can take a contested technical question across several teams to a decision, and write it down.
Ways to stand out from the crowd:
- Experience with GPU clusters for AI training at scale: thousands of GPUs, large training runs, high-speed interconnects.
- Experience with reinforcement learning or post-training workloads and what they need from infrastructure.
- Contributions to open-source infrastructure projects, or experience taking an internal platform open source.
- Has led teams across time zones.
- Uses AI coding and operations tools in daily work and has raised a team's productivity with them.
224,000 USD – 356,500 USD for Level 3; and 272,000 USD – 431,250 USD for Level 4.
You will also be eligible for equity and benefits.
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.