Senior AI Infrastructure Engineer - Training Platform

As a Software Engineer on the Machine Learning Infrastructure team, you will

build the "Operating System" for our large-scale GPU clusters. You will

architect a high-performance training platform that handles the immense

complexity of multi-thousand GPU workloads, ensuring every cycle is used

efficiently. Your work directly determines the velocity at which our researchers

can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the

orchestration, networking, and reliability challenges that emerge at massive

scale. You will partner closely with researchers to build a seamless, resilient

environment that transforms raw compute into breakthrough AI.

YOU WILL:

* Architect and scale a multi-tenant orchestration layer that abstracts away

the complexity of GPU clusters, ensuring high utilization and seamless job

recovery.

* Design and implement scheduling primitives to optimize the lifecycle of

training jobs.

* Develop deep observability and automated health-checking into the training

stack to proactively identify and isolate hardware failures

* Evaluate and integrate emerging technologies in the CNCF and AI ecosystem

(e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance

velocity with long-term maintainability.

* Work closely with Finance and Procurement teams to drive our capacity

planning process.

* Participate in our team’s on call process to ensure the availability of our

services.

* Own projects end-to-end, from requirements, scoping, design, to

implementation, in a highly collaborative and cross-functional environment.

IDEALLY YOU'D HAVE:

* 5+ years of experience in backend or infrastructure engineering, with at

least 2 years focused on orchestrating ML workloads at scale (100+ GPU

nodes).

* Strong programming skills in one or more languages (e.g. Python, Go, Rust,

C++)

* Experience with complex compute management systems that cover queueing,

quotas, preemption, and gang scheduling.

* Experience with distributed training infrastructure, such as EFA, Infiniband,

and topology-aware scheduling.

* Experience with distributed storage systems (e.g. Lustre, S3) as they relate

to training throughput

* Expert-level knowledge of Kubernetes internals (Custom Resources, Operators,

Admission Controllers) and how they interact with device plugins for

specialized hardware.

* Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code

(e.g., Terraform).

* Proven ability to solve complex problems and work independently in

fast-moving environments.

NICE TO HAVES:

* Experience with distributed training techniques such as DeepSpeed, FSDP, etc.

* Experience with the NVIDIA software and hardware stack (CUDA, NCCL)

* Experience with PyTorch

* Familiarity with post-training algorithms such as GRPO, and with

Reinforcement Learning

Compensation

packages at Scale for eligible roles include base salary, equity,

and benefits. The range displayed on each job posting reflects the minimum and

maximum target for new hire salaries for the position and may be inclusive of

several career levels at Scale; it will be determined during the interview

process based on work location and additional factors, including job-related

skills, experience, qualifications, interview performance, and relevant

education or training. Scale employees in eligible roles are also granted equity

based compensation, subject to Board of Director approval. Your recruiter can

share more about the specific salary range for your preferred location during

the hiring process, and confirm whether the hired role will be eligible for

equity grant. You'll also receive benefits including, but not limited to:

comprehensive health, dental and vision coverage, retirement benefits, a

learning and development stipend, and generous PTO. Additionally, this role may

be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be

located. For pay transparency purposes, the base salary range for this full-time

position in the locations of San Francisco, New York, Seattle is:

$216,000—$270,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering

candidates for the same role. This allows us to ensure a fair and thorough

evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most

important decisions. Our products provide the high-quality data and full-stack

technologies that power the world's leading models, and help enterprises and

governments build, deploy, and oversee AI applications that deliver real impact.

We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic,

Time Inc., the Government of Qatar, and U.S. government agencies including the

Army and Air Force. We are expanding our team to accelerate the development of

AI applications.

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which is why we are proud to be an inclusive and equal opportunity workplace. We

are committed to equal employment opportunity regardless of race, color,

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marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to

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a reasonable accommodation in the application or recruiting process due to a

disability, please contact us at [email protected]. Please see the United

States Department of Labor's Know Your Rights poster

[https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf]

for additional information.

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