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Remote Nvidia Hardware Engineer Jobs in Silver Spring, MD

Shift5

Systems Integration Engineer

Arlington, VA · On-site +1

$141K - $160K/yr

It requires technical fluency in hardware/software integration, ownership of formal government ... Flexible work & remote work policy * Tax-deferred public transit benefits with Metro SmartBenefits ...

Shift5

Systems Integration Engineer

Rosslyn, VA · On-site +1

$141K - $160K/yr

It requires technical fluency in hardware/software integration, ownership of formal government ... Flexible work & remote work policy * Tax-deferred public transit benefits with Metro SmartBenefits ...

Maximus

CAL Test Engineer

Mclean, VA · On-site +1

This role is hybrid, allowing for remote work, but requires the ability to work onsite in Tyson ... hardware changes within the Client Access Lab (CAL). The role supports physical and virtual test ...

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All JobsNvidia Hardware Engineer JobsRemote Nvidia Hardware Engineer JobsRemote Nvidia Hardware Engineer Jobs in Silver Spring, MD

Remote Nvidia Hardware Engineer information

See Silver Spring, MD salary details

$52.7K

$151.2K

$203.1K

How much do remote nvidia hardware engineer jobs pay per year?

As of Jul 18, 2026, the average yearly pay for remote nvidia hardware engineer in Silver Spring, MD is $151,169.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,700.00 and $168,500.00 per year, depending on experience, location, and employer.

What does a Remote Nvidia Hardware Engineer do?

A Remote Nvidia Hardware Engineer focuses on designing, developing, and testing hardware components and systems for Nvidia products, such as graphics processing units (GPUs) and related technologies, while working from a remote location. They collaborate with cross-functional teams to ensure hardware solutions meet performance, reliability, and efficiency standards. Their work may include circuit design, board layout, hardware debugging, and supporting the integration of Nvidia hardware into various devices. Remote engineers use digital communication and collaboration tools to work effectively with global teams and contribute to innovative hardware solutions.

What is the difference between Remote Nvidia Hardware Engineer vs Remote Nvidia Software Engineer?

AspectRemote Nvidia Hardware EngineerRemote Nvidia Software Engineer
Required CredentialsBachelor's or higher in Electrical Engineering, Computer Engineering, or related; hardware design certificationsBachelor's or higher in Computer Science, Software Engineering, or related; programming certifications
Work EnvironmentDesigning and testing hardware components, collaborating with hardware teamsDeveloping software, drivers, and algorithms for Nvidia products
Industry UsageHardware development for GPUs, AI accelerators, and embedded systemsSoftware development for drivers, SDKs, and AI frameworks

The main difference is that Remote Nvidia Hardware Engineers focus on designing and testing physical hardware components, while Remote Nvidia Software Engineers develop the software that runs on Nvidia hardware. Both roles require technical expertise but differ in their focus areas within the Nvidia ecosystem.

What are some common challenges faced by Remote Nvidia Hardware Engineers, and how can they be addressed?

Remote Nvidia Hardware Engineers often encounter challenges related to effective collaboration and communication, especially when working on complex hardware design and testing with distributed teams. Staying aligned with project milestones, ensuring access to necessary hardware resources, and troubleshooting remotely can also be demanding. These challenges can be addressed by leveraging robust collaboration tools, maintaining clear documentation, and scheduling regular virtual meetings to synchronize efforts. Additionally, using remote desktop solutions and cloud-based simulation environments can help bridge the gap when physical access to hardware is limited.

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

To thrive as a Remote Nvidia Hardware Engineer, you need a strong background in electrical or computer engineering, experience with GPU architecture, and proficiency in hardware design and validation. Expertise with tools such as Verilog/VHDL, simulation environments, and familiarity with Nvidia’s development platforms or relevant certifications is common. Strong problem-solving abilities, effective remote communication, and collaborative teamwork skills set top candidates apart. These competencies ensure efficient development, troubleshooting, and innovation in high-performance hardware solutions within distributed teams.
What are the most commonly searched types of Nvidia Hardware Engineer jobs in Silver Spring, MD? The most popular types of Nvidia Hardware Engineer jobs in Silver Spring, MD are:
What are popular job titles related to Remote Nvidia Hardware Engineer jobs in Silver Spring, MD? For Remote Nvidia Hardware Engineer jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Remote Nvidia Hardware Engineer jobs in Silver Spring, MD look for? The top searched job categories for Remote Nvidia Hardware Engineer jobs in Silver Spring, MD are:
Remote Nvidia Hardware Engineer jobs near you
Infographic showing various Remote Nvidia Hardware Engineer job openings in Silver Spring, MD as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $151,169 per year, or $72.7 per hour.

Software Engineer - TS/SCI with Poly

Staffed4U

Annapolis Junction, MD • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 days ago

Job description

Software Engineer
$160k- $230k

Location: Annapolis Junction, MD
Clearance Required: TS/SCI with Polygraph
Experience Level: 7+ years of experience
Education: Bachelor's degree in Computer Science, Engineering, or related field
Position Summary:
We are seeking a skilled and mission-driven Software Engineer to support the ML Frameworks team. In this role, you will contribute to the design, development, and deployment of a Retrieval-Augmented Generation (RAG) solution within a high-performance computing (HPC) Linux environment. This position is ideal for someone with a strong Linux background and a passion for AI/ML technologies, especially Large Language Models (LLMs) and secure AI systems.
Primary Responsibilities:

  • Contribute to the development and deployment of secure RAG pipelines in an HPC Linux environment
  • Work with cutting-edge AI/ML technologies, including LLM orchestration frameworks, embedding models, and inference platforms
  • Develop and maintain services using Python and Golang
  • Build and manage containerized services using Docker, Podman, and containerd
  • Deploy services using orchestration tools like Kubernetes and Docker Compose
  • Automate and monitor workflows with CI/CD pipelines, using GitLab CI and version control with Git
  • Integrate monitoring tools such as Prometheus and Grafana for performance and reliability
  • Participate in system administration, including Linux CLI, shell scripting, and general support tasks
Required Qualifications:
  • Active TS/SCI clearance with Polygraph
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field
  • 7+ years of professional software engineering experience
  • Strong experience with Linux system administration, CLI, and shell scripting
  • Proficiency in Python and Golang
  • Familiarity with RAG pipelines, LLMs, and knowledge retrieval systems
  • Experience with containerization technologies and orchestration tools (Docker, PodMan, Kubernetes, Docker Compose)
  • Solid understanding of CI/CD principles and related tools (GitLab CI)
  • Experience with metrics and monitoring tools (e.g., Prometheus, Grafana)
  • Experience using Git for version control
Desired Skills & Technologies:
  • Experience with GPU-enabled applications and debugging tools
  • Familiarity with LLM orchestration frameworks and OpenAPI
  • Experience with distributed processing frameworks such as Spark, Dask, or Ray
  • Familiarity with SQL, Elasticsearch, and vector databases
  • Experience with HTMX or Hyperscript
  • Understanding of multi-node, multi-GPU AI training environments
  • Knowledge of AI inferencing platforms such as Nvidia NIM/TRITON, vLLM, or Ray-based deployment
  • Experience with the Atlassian suite (Confluence, Jira)

Our client offers a highly competitive and comprehensive benefits package designed to support your personal and professional growth, while promoting a healthy work-life balance. Benefits include:

  • 100% Employer-Paid Health, Dental, and Vision Insurance – Full coverage for employees

  • Zero Vesting 401(k) Plan with 10% Company Contribution – Immediate access to all contributions

  • 31 Days of Paid Time Off – Includes vacation, personal time, and all federal holidays

  • Student Loan Repayment Assistance – Helping you pay down your educational debt

  • Unlimited Certification & Training Support – Invest in your professional development

  • Flexible Work Environment – Remote work options and flexible scheduling available

  • Multiple Incentive Bonuses – Performance-based rewards throughout the year

  • Exclusive Company Memberships – Access to curated memberships and employee perks

This package reflects our client’s commitment to empowering their employees with meaningful benefits and recognizing outstanding performance.
 


We are an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other protected status under applicable law.