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Remote Nvidia Engineering Jobs in Virginia (NOW HIRING)

Data Engineer

Arlington, VA · On-site +1

$62K - $141K/yr

Remote Work: Hybrid Job Number: R0247120 Location: Arlington,VA,US Share job via: Share Data ... Master's degree in Computer Science, Computer Engineering, Mathematics, Data Science, Software ...

Data Engineer

Arlington, VA · On-site +1

$62K - $141K/yr

Remote Work: Hybrid Job Number: R0241523 Location: Arlington,VA,US Share job via: Share Data ... Master's degree in CS, Computer Engineering, Mathematics, Data Science, Software Engineering ...

Remote Nvidia Engineering information

What is a remote Nvidia engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are the key skills and qualifications needed to thrive as a remote Nvidia engineer, and why are they important?

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

What are the most commonly searched types of Nvidia Engineering jobs in Virginia?

The most popular types of Nvidia Engineering jobs in Virginia are:

What job categories do people searching Remote Nvidia Engineering jobs in Virginia look for?

The top searched job categories for Remote Nvidia Engineering jobs in Virginia are:

What cities in Virginia are hiring for Remote Nvidia Engineering jobs?

Cities in Virginia with the most Remote Nvidia Engineering job openings:

Infographic showing various Remote Nvidia Engineering job openings in Virginia as of September 2026, with employment types broken down into 86% Full Time, 9% Part Time, and 5% Contract. Highlights an 100% Remote job distribution.

Senior Machine Learning Engineer, Radar & Remote Sensing

Chantilly, VA • On-site, Remote

NT Concepts
IT Services • 51 - 200 employees

$128K - $177K/yr

Full-time

Posted 20 days ago


Job description

Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. We're looking for the best and the brightest to join us in supporting this mission. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, join our growing team and discover What's Next for you. We tackle hard problems to meet our clients' needs.

We are looking for an applied engineer to own our radar and ML technical stack. This is a blended role at the intersection of radar/SAR simulation, machine learning, scientific software, and compute infrastructure.

The ideal candidate is not a pure data scientist or a pure signal processing engineer. They are a technical owner who can move across the stack: from radar simulations and data preprocessing to ML model development, local GPU/compute setup, and hand-offs of radar products to software and hardware teams.

Clearance: Active TS/SCI clearance. US Citizenship is required.

Location: Chantilly, VA (Monday-Thursday Onsite & Friday Remote)

Responsibilities: 

  • Act as a technical liaison, fostering effective communication and collaboration between radar engineering, machine learning, software engineering, and operation teams. 
  • Develop and maintain robust radar and SAR simulation pipelines, including synthetic data generation, scene/return modeling, and validation workflows.
  • Design, build and refine end-to-end ML models and pipelines for radar-related tasks, including preprocessing, training, evaluation, and deployment-ready packaging.
  • Utilize and analyze defense-focused datasets, including radar, 3D models, Electro-Optical/Infrared (EO/IR), and sensing-adjacent data.
  • Create radar products and technical deliverables for internal software teams and hardware partners, including APIs, data schemas, containers, documentation, and integration guidance.
  • Design, configure, and optimize local compute environments, including GPU/eGPU setups, remote compute, storage, networking, containerization, and benchmarking.
  • Support ML inference/training on constrained or embedded compute, with awareness of systems such as RFSoCs, FPGAs, and related hardware constraints.
  • Collaborate with RF/hardware partners to support internal RF code processing, radar outputs, and productization of deployable radar hardware
  • Help deploy and maintain web applications and internal tools on classified or restricted networks.
  • Contribute to technical writing, SBIR proposals, and system documentation.

 Required Qualifications: 

  • Deep experience in Synthetic Aperture Radar, non-imaging radar, remote sensing, or signal processing
  • Solid understanding of radar/SAR fundamentals, including:
    • I/Q and complex-valued data
    • Simulation techniques
    • Image formation algorithms and radar-to-image pipelines
    • Coherent vs. incoherent processing
  • Proven track record of experience with radar or remote sensing simulations
  • Strong proficiency with scientific Python libraries:
    • NumPy, PyTorch, SciPy, Matplotlib, Jupyter, and related scientific stacks
  • Demonstrated ability to build end- to-end ML pipelines encompassing:
    • Data preprocessing
    • Training
    • Evaluation
    • Versioning
    • Packaging
    • Hand-off to other engineers
  • Hands-on experience with GPU compute, such as:
    • PyTorch
    • CUDA
    • NVIDIA tooling
    • Remote GPU Servers
    • Local GPU compute
  • Ability to explain radar/ML concepts to non-radar engineers and produce clear technical deliverables
  • Adherence to robust software engineering principles and best practices (e.g. clean code, testing, version control).
  • Exceptional communication skills, with the ability to clearly articulate complex radar and ML concepts to both technical and non-technical audiences, and to produce high-quality technical documentation and deliverables.

 Preferred Skills/Experience:

  • Experience with Xpatch simulations specifically
  • Experience with CAD and or artistic 3D modeling skills
  • Experience with EO/IR or multi-sensor fusion
  • Experience with adversarial imaging AI
  • Understanding of RFSoCs, FPGAs, HLS, quantization, or edge deployment constraints
  • Experience designing or optimizing local compute servers / GPU clusters / eGPU configurations
  • Experience working with RF hardware partners or hardware-in-the-loop systems
  • Experience with LLMs, LoRA fine-tuning, or local model deployment for niche tasks
  • Experience with container computing and orchestration

Physical Requirements: 

  • Prolonged periods sitting at a desk and working on a computer 
  • Must be able to lift up to 10-15 pounds at time 

#JT