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Staff AI Training Infrastructure Engineer

designworkstalentBellevueEngineering
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Experience
Senior
Posted
2 Oct 2026
Status
Open · checked 7d ago

About this role

Staff AI Training Infrastructure Engineer is a hybrid role based in the Bellevue, Washington area that involves building and scaling distributed systems for large-scale artificial intelligence model training. This position suits engineers who want to work on distributed computing, GPU clusters, and foundational cloud platforms for AI.

Role Overview

This foundational engineering position focuses on developing the infrastructure layer that supports large-scale artificial intelligence training workloads. The professional in this role works on distributed training systems, graphics processing unit clusters, model pipelines, and the tooling required to make artificial intelligence development scalable and reliable. The position involves collaborating with infrastructure, orchestration, performance, and machine learning teams to solve challenges related to fault tolerance and training efficiency.

Key Responsibilities

Build and scale distributed training infrastructure supporting large models across large graphics processing unit clusters.
Design and improve systems that increase training reliability, efficiency, and resource utilization.
Develop solutions for fault tolerance, checkpointing, recovery, and large-scale training operations.
Integrate artificial intelligence models into production training pipelines in partnership with platform and engineering teams.
Diagnose and resolve issues impacting training throughput, stability, reliability, and cost efficiency.
Build tools and automation that improve the developer experience for researchers and engineers.
Establish best practices for training infrastructure, operational processes, and platform reliability.
Contribute to the evolution of the platform as an early member of the engineering team.

Requirements

Hands-on experience building and operating distributed training systems or large-scale machine learning infrastructure.
Experience supporting large artificial intelligence models, foundation models, post-training workflows, or similar machine learning systems.
Understanding of reliability, scalability, and efficiency challenges associated with multi-node graphics processing unit training.
Experience integrating training systems with production machine learning pipelines.
Programming skills and experience working with complex distributed systems.
Ability to independently own technically challenging projects in a fast-moving engineering environment.
Comfort operating with high ownership and limited process overhead.

Nice to Have

Experience with distributed training frameworks such as PyTorch Distributed, DeepSpeed, Megatron-LM, or Ray.
Experience with supervised fine-tuning, reinforcement learning from human feedback, or other post-training workflows.
Background operating artificial intelligence training infrastructure at scale within a hyperscaler, research organization, cloud provider, or graphics processing unit cloud environment.
Experience optimizing graphics processing unit utilization, training performance, or distributed system reliability.
Familiarity with Kubernetes, containerized artificial intelligence workloads, and large-scale infrastructure platforms.

Skills and Tools

PyTorch Distributed
DeepSpeed
Megatron-LM
Ray
Kubernetes
Distributed training systems
Graphics processing unit clusters

Salary and Benefits

Competitive base pay for the Bellevue market with eligibility for merit increases, annual bonuses, and long-term incentives based on individual performance.
Medical, dental, and vision insurance for United States based employees.
A 401(k) plan with company match and paid holidays.

About the Company

The organization is a well-funded, rapidly growing artificial intelligence infrastructure company backed by significant long-term investment. It combines the speed and innovation of a startup with the stability of an established parent organization.

How to Apply

Interested candidates should apply on the official company careers page.

Skills and tech stack

PyTorch DistributedDeepSpeedMegatron-LMRayKubernetesPyTorchReinforcement LearningMachine LearningFine-tuningDistributed Systems

Questions candidates ask

Where is the job located?

The role is hybrid and based in the Bellevue, Washington area, requiring approximately three days per week in the office.

Is visa sponsorship available?

No, United States work authorization is required and visa sponsorship is not currently available.

What type of experience is required?

Candidates need hands-on experience building and operating distributed training systems or large-scale machine learning infrastructure, along with experience supporting large artificial intelligence models or foundation models.

What benefits are included?

United States based employees have access to medical, dental, and vision insurance, a 401(k) plan with company match, and paid holidays.

Ready to apply?

The application is on the official designworkstalent careers page.

Apply on company site