ZipRecruiter

Log In

2

Remote Gpu Engineer Jobs in Washington (NOW HIRING)

ManTech

AI Engineer

Washington, DC · On-site +1

$141K - $236K/yr

Manage and optimize Kubernetes-based AI deployments, focusing on GPU inference optimization ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

Leidos

Senior Systems Engineer

Bethesda, MD · On-site +1

$131K - $237K/yr

Percentage of remote work will vary based on client requirements/deliverables. As a senior member ... Broad understanding of GPU-enabled systems architecture and engineering, including GPU integration ...

Constellis

DevOps Engineer

VA · On-site +1

$55.75 - $76.25/hr

Work is typically based in a remote office environment and subject to frequent interruptions ... Hands-on experience with Jenkins, Nvidia GPU toolkits, or broader DevOps toolchains * Monitoring ...

Constellis

DevOps Engineer

VA · On-site +1

$55.75 - $76.25/hr

Work is typically based in a remote office environment and subject to frequent interruptions ... Hands-on experience with Jenkins, Nvidia GPU toolkits, or broader DevOps toolchains * Monitoring ...

Bright Vision Technologies

ML Data Engineer

Herndon, VA · Remote

$100K - $150K/yr

ML Data Engineer - Remote Bright Vision Technologies is a technology consulting and software ... Build high-throughput data loading systems that maximize GPU utilization during training.

next page

Showing results 1-20

All JobsGpu Engineer JobsRemote Gpu Engineer JobsRemote Gpu Engineer Jobs in Washington

Remote Gpu Engineer information

What are the key skills and qualifications needed to thrive as a Remote GPU Engineer, and why are they important?

To thrive as a Remote GPU Engineer, you need strong expertise in GPU architectures, parallel programming (CUDA/OpenCL), and a solid background in computer science or engineering. Familiarity with tools like CUDA Toolkit, performance profilers, and version control systems, as well as experience with relevant certifications, is typically required. Excellent problem-solving abilities, communication skills, and the capacity to collaborate effectively in remote, distributed teams are standout soft skills. These competencies ensure efficient GPU solution development, effective troubleshooting, and seamless teamwork in a remote engineering environment.

What are Remote GPU Engineers?

Remote GPU Engineers are specialized software or hardware engineers who work primarily with Graphics Processing Units (GPUs) from a remote location. They focus on designing, optimizing, and maintaining GPU-based systems for applications such as machine learning, high-performance computing, and graphics rendering. These professionals often collaborate with teams virtually, leveraging cloud-based GPU resources and remote access tools. Their work enables companies to efficiently utilize GPU technology without requiring engineers to be on-site.

What are some common challenges faced by Remote GPU Engineers when collaborating with distributed teams?

Remote GPU Engineers often work with global teams, which can present challenges such as coordinating across different time zones, ensuring consistent communication, and managing access to high-performance hardware remotely. To overcome these hurdles, it's important to leverage collaboration tools, maintain clear documentation, and establish regular check-ins. Additionally, using remote desktop solutions and cloud-based GPU environments can help facilitate smoother development and debugging processes.
What are the most commonly searched types of Gpu Engineer jobs in Washington? The most popular types of Gpu Engineer jobs in Washington are:
What are popular job titles related to Remote Gpu Engineer jobs in Washington? For Remote Gpu Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Remote Gpu Engineer jobs in Washington look for? The top searched job categories for Remote Gpu Engineer jobs in Washington are:
What cities in Washington are hiring for Remote Gpu Engineer jobs? Cities in Washington with the most Remote Gpu Engineer job openings:
Remote Gpu Engineer jobs near you
Infographic showing various Remote Gpu Engineer job openings in Washington as of June 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 100% Remote job distribution.

Intelligent Infrastructure Engineer

Bright Vision Technologies

Herndon, VA • On-site, Remote

$100K - $150K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Intelligent 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: Intelligent Infrastructure Engineer
Location: 100% Remote (United States)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$150,000 Annually
Experience: 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 Intelligent 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 boon@bvteck.com or contact us at (908) 650-6699. 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.

Apply