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Remote Ai Infrastructure Engineer Jobs in Seattle, WA

Designworks Talent

AI Training Infrastructure Engineer

Bellevue, WA · Remote

$110K - $144K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

AI Training Infrastructure Engineer Location: Hybrid | Bellevue, WA Area Titles: Senior and Staff (multiple roles available) Build the Training Infrastructure Powering Next-Generation AI Models About ...

The AES Group

Infrastructure Engineer

Seattle, WA · Remote

$110K - $144K/yr

  • Medical

  • Dental

  • Vision

Role - Infrastructure Engineer Location - Remote, USA Let's create our future together at The AES ... AI, and other emerging technologies. Why Join The AES Group, Inc. * Competitive compensation ...

Headway

Staff Infrastructure Engineer

Seattle, WA · On-site +1

$265K - $331K/yr

Infrastructure Engineering is one of three teams in Engineering Foundations, alongside Agentic ... As AI dramatically increases code velocity across the org, our mandate is to make every change safe ...

New

Porch.com, Inc.

Infrastructure Engineering Team Lead

Seattle, WA · On-site +1

$122K - $160K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Remote Job Summary The future is bright for the Porch Group, and we'd love for you to be a part of it as our Infrastructure Engineering Lead . Rynoh - a business unit of Porch - is a rapidly growing ...

Porch.com, Inc.

Infrastructure Engineering Team Lead

Seattle, WA · On-site +1

$122K - $160K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Remote Job Summary The future is bright for the Porch Group, and we'd love for you to be a part of it as our Infrastructure Engineering Lead . Rynoh - a business unit of Porch - is a rapidly growing ...

Nvidia

Senior Compiler Engineer Infrastructure

Redmond, WA · On-site +1

$121K - $165K/yr

Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era ... Design and build infrastructure, tooling, and developer workflows that improve productivity ...

Designworks Talent

Data Center Network Engineer

Bellevue, WA · Remote

  • Medical

  • Dental

  • Vision

  • Retirement

The organization is developing a comprehensive AI infrastructure, platform, and services portfolio ... Engineering teams are intentionally lean, highly collaborative, and AI-native, leveraging modern ...

Wsgr

Principal Cloud Infrastructure Engineer

Seattle, WA · On-site +1

$147K - $198K/yr

The Principal Cloud Infrastructure Engineer, under the direction of the Senior manager of ... This role can be hybrid or virtual/remote. Essential Duties and Responsibilities: * Act as the ...

Oracle

Senior Manager, Core Infrastructure Engineering

Seattle, WA · On-site +1

$123K - $167K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... remote persistent storage solution with the latency and performance comparable to that of a local ... And with AI embedded across our products and services, we help customers turn that promise into a ...

Oracle

Senior Manager, Core Infrastructure Engineering

Seattle, WA · On-site +1

$123K - $167K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... remote persistent storage solution with the latency and performance comparable to that of a local ... And with AI embedded across our products and services, we help customers turn that promise into a ...

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All JobsAi Infrastructure Engineer JobsRemote Ai Infrastructure Engineer JobsRemote Ai Infrastructure Engineer Jobs in Seattle, WA

Remote Ai Infrastructure Engineer information

See Seattle, WA salary details

$52.9K

$144.6K

$207.1K

How much do remote ai infrastructure engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for remote ai infrastructure engineer in Seattle, WA is $144,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,300.00 and $160,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote AI infrastructure engineer?

To thrive as a Remote AI Infrastructure Engineer, you need expertise in cloud computing, distributed systems, and software engineering, often supported by a degree in computer science or a related field. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud platforms such as AWS, Azure, or GCP is typically required, along with knowledge of CI/CD pipelines and AI/ML frameworks. Strong problem-solving skills, self-motivation, and effective remote communication are essential soft skills for success in this role. These skills ensure robust, scalable AI infrastructure that supports rapid innovation and seamless collaboration across distributed teams.

What is a remote AI infrastructure engineer?

A Remote AI Infrastructure Engineer is a professional who designs, builds, and maintains the systems and tools necessary to support artificial intelligence (AI) projects, all while working remotely. Their responsibilities often include developing and optimizing cloud or on-premise infrastructure, ensuring scalability, managing data pipelines, and supporting machine learning workflows. They work closely with data scientists and software engineers to ensure AI models can be efficiently trained, deployed, and monitored in production environments. The remote aspect allows them to perform these tasks from anywhere, using collaboration tools and cloud platforms.

What are some common challenges faced by remote AI infrastructure engineers, and how can they be addressed?

Remote AI Infrastructure Engineers often encounter challenges such as managing distributed systems, ensuring robust data pipelines, and maintaining high system reliability across different time zones. Collaboration with cross-functional teams can require clear communication and effective use of remote tools. To address these challenges, it's important to establish strong documentation practices, schedule regular check-ins, and utilize automated monitoring and deployment solutions. Staying proactive and adaptable helps ensure seamless infrastructure performance and team alignment.

What are the most commonly searched types of Ai Infrastructure Engineer jobs in Seattle, WA?

The most popular types of Ai Infrastructure Engineer jobs in Seattle, WA are:

What are popular job titles related to Remote Ai Infrastructure Engineer jobs in Seattle, WA?

For Remote Ai Infrastructure Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Remote Ai Infrastructure Engineer jobs in Seattle, WA look for?

The top searched job categories for Remote Ai Infrastructure Engineer jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Remote Ai Infrastructure Engineer jobs?

Cities near Seattle, WA with the most Remote Ai Infrastructure Engineer job openings:

Remote Ai Infrastructure Engineer jobs near you
Infographic showing various Remote Ai Infrastructure Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 11% In-person, and 89% Remote job distribution, with an average salary of $144,605 per year, or $69.5 per hour.

ML Infrastructure Engineer

Bright Vision Technologies

Bellevue, WA • On-site, Remote

$150K/yr

Full-time

Posted 5 days ago

Job description

ML Infrastructure Engineer - Remote 
 
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. 
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. 
 
Job Title: ML Infrastructure Engineer
Location: 100% Remote (U.S.) 
Position Type: Full-time, Direct W2 
Salary Range: $100,000–$150,000 Annually 
Experience Required: 6+ years 
 
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. 
 
Job Summary 
We are seeking an AI Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads. The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with strong emphasis on reliability, efficiency, and cost control. The ideal candidate has built or operated production AI infrastructure at scale, understands the interaction between hardware, kernel, scheduler, and ML framework, and brings strong software engineering discipline to platform work. 
Key Responsibilities 
  • Design and operate GPU and accelerator infrastructure for training and inference, spanning on-prem clusters, cloud-managed services, and hybrid configurations. 
  • Build scheduling, queueing, and resource-sharing systems that maximize accelerator utilization across many teams. 
  • Integrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform offering. 
  • Operate high-performance storage systems and data pipelines that keep accelerators fed with training data at near-line-rate. 
  • Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth collective communication. 
  • Build observability for AI workloads including utilization, throughput, training stability, and failure-mode analytics. 
  • Implement checkpointing, restart, and fault-tolerance patterns for long-running training jobs at scale. 
  • Drive cost optimization across compute, storage, and networking through scheduling, spot capacity, and right-sizing. 
  • Develop developer tooling and paved-road workflows that let researchers launch experiments safely and efficiently. 
  • Partner with research and applied ML teams to plan capacity for upcoming training runs. 
  • Implement security controls, isolation, and access management for multi-tenant AI infrastructure. 
  • Drive automation across cluster provisioning, lifecycle management, and configuration enforcement. 
  • Maintain runbooks, capacity dashboards, and operational documentation for the AI platform. 
  • Stay current with AI infrastructure research, accelerator hardware, and emerging open-source AI tooling. 
Required Qualifications 
  • Bachelor’s or Master’s degree in Computer Science or a related field. 
  • Six or more years of experience in infrastructure, platform, or HPC engineering. 
  • Hands-on experience operating GPU clusters or large-scale ML training infrastructure. 
  • Strong proficiency in Python and at least one systems language such as Go or C++. 
  • Deep understanding of distributed training, accelerator architectures, and collective communication. 
  • Experience with Kubernetes, Slurm, Ray, or similar scheduling systems for ML workloads. 
  • Strong understanding of Linux internals, networking, and high-performance storage. 
  • Experience with at least one major cloud provider’s ML infrastructure offerings. 
  • Strong software engineering practices including testing, CI/CD, and code review. 
  • Excellent communication and cross-functional collaboration skills. 
Preferred Qualifications 
  • Experience operating InfiniBand or RDMA networking at scale. 
  • Contributions to open-source ML infrastructure projects. 
  • Familiarity with custom orchestrators or research-grade training stacks. 
  • Exposure to frontier model training operations. 
  • Experience with FinOps for AI workloads. 
How to Apply 
Would you like to know more about this opportunity? For immediate consideration, please send your resume to Jenny@bvteck.com or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
 

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees\' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

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