ZipRecruiter

Log In

1

Gpu Jobs in Virginia (NOW HIRING)

Leidos

Senior Computer Systems Engineer

Arlington, VA · On-site

$131K - $237K/yr

Broad understanding of GPU-enabled systems architecture and engineering, including GPU integration, virtualization, Multi-Instance GPU (MIG), and associated software stacks.Experience with creating ...

previous pagenext page

Showing results 21-40

All JobsGpu JobsGpu Jobs in Virginia

Gpu information

What is a GPU?

A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images and graphics for display. While originally developed for rendering graphics in video games and visual applications, GPUs are now widely used for parallel processing tasks in areas such as artificial intelligence, data science, and scientific computing. Their architecture allows them to handle thousands of operations simultaneously, making them much faster than traditional CPUs for certain workloads.

What is a GPU engineer?

A GPU job refers to a computing task that utilizes a Graphics Processing Unit (GPU) for acceleration. GPUs are specialized processors designed for parallel processing, making them ideal for tasks like machine learning, scientific simulations, and rendering. Many software applications offload intensive computations to GPUs to improve performance and efficiency. Jobs related to GPUs can involve programming, optimization, and hardware configuration in fields like AI, gaming, and data analysis.

What are the key skills and qualifications needed to thrive as a GPU engineer?

To thrive as a GPU Engineer, you need a solid background in computer engineering, mathematics, and programming languages such as C++ or CUDA, often supported by a relevant degree. Familiarity with GPU architectures, parallel computing frameworks, and tools like OpenCL or Vulkan is typically required. Analytical thinking, problem-solving, and teamwork are essential soft skills for innovating and debugging complex systems. These abilities are crucial for optimizing performance, ensuring compatibility, and driving advancements in graphics and computational workloads.

What are some common challenges faced by GPU engineers when optimizing performance for various applications?

GPU engineers often encounter challenges such as balancing high computational throughput with power efficiency, ensuring compatibility across different hardware architectures, and optimizing code for parallel processing. They must also troubleshoot bottlenecks in memory bandwidth and latency that can impact performance. Collaboration with software developers and hardware architects is crucial to identify and resolve these issues, and staying updated with the latest advances in GPU technologies is essential for continued success.

What is the difference between Gpu vs Data Scientist?

AspectGpuData Scientist
Required CredentialsKnowledge of parallel computing, programming skills (CUDA, OpenCL)Degree in Computer Science, Statistics, or related fields; programming skills
Work EnvironmentHardware-focused, technical, often in R&D or engineering teamsData analysis, modeling, research in various industries
Industry UsageTech, gaming, AI, machine learningFinance, healthcare, tech, marketing

Gpu specialists focus on hardware and parallel processing for computing tasks, while data scientists analyze data to extract insights. Both roles require technical skills, but Gpu roles are more hardware-oriented, whereas data scientists focus on data analysis and modeling.

How to get into the graphics processing unit industry?

To enter the GPU industry, candidates typically need a strong background in computer engineering, electrical engineering, or computer science, with skills in programming languages like C++ and knowledge of graphics APIs such as DirectX or Vulkan. Relevant experience can be gained through internships, projects, or certifications in hardware design, GPU architecture, or related fields. Staying updated on industry developments and obtaining certifications like NVIDIA's or AMD's developer programs can also enhance job prospects.

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

The most popular types of Gpu jobs in Virginia are:

What are popular job titles related to Gpu jobs in Virginia?

For Gpu jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Gpu jobs in Virginia look for?

The top searched job categories for Gpu jobs in Virginia are:

Gpu jobs near you
Infographic showing various Gpu job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 92% Full Time, 4% Part Time, and 3% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

Senior Machine Learning Engineer, Radar & Remote Sensing

NT Concepts

Chantilly, VA • On-site, Remote

$107K - $146K/yr

Full-time

Posted 17 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
The pay range listed for this position reflects the wage or salary range NT Concepts expects to pay for this role at the time of posting. The compensation offered to a successful candidate within this range will be based on legitimate, job-related factors, including (but not limited to) the candidate's work location, education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements.
Virginia Pay Range
$131,376-$243,984 USD
About NT Concepts
Founded in 1998 and headquartered in the Washington DC Metro area, NT Concepts is a private, mid-tier company with clients spanning the Intelligence and Defense communities. We deliver end-to-end data and technology solutions that advance the modernization, transformation, and automation of the national security mission-solutions with real impact developed in a strong engineering culture that encourages technical growth, leadership, and creative "big idea" problem-solving.
Employees are the core of NT Concepts. We understand that world-changing concepts happen in collaborative environments. We are a company where talented teams work together using innovation and expertise to solve our clients' most critical challenges. Here, you'll gain competitive benefits, opportunities to bolster your skills and develop new abilities, and a company culture dedicated to support and service. In addition to our benefits program, we encourage our employees to take part in #NTC_GivesBack, which paves the way for positive social change.
If joining a stable company with strong professional growth opportunities resonates with you, and you seek vital, mission-driven projects (for some pretty cool clients) that use your specific talents, we'd love to have you move forward with us.

Apply