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Nvidia Engineering Jobs in Washington, DC (NOW HIRING)

Via Logic LLC

Senior AI Engineer

Rockville, MD · On-site

$130 - $160/hr

Contribute to the integration of AI, DevSecOps, data engineering, platform engineering ... NVIDIA GPU ecosystems * Vector databases Commitment to Non‑Discrimination All qualified ...

Booz Allen Hamilton

Autonomy SME, Lead

Washington, DC · On-site

$62.25 - $85.50/hr

... Engineering field Preferred : • Experience working in military exercises and war games • Experience with autonomy frameworks such as Hivemind, PX4, ArduPilot, NVIDIA Isaac, or ROS2 • Experience ...

BOOZ, ALLEN & HAMILTON, INC.

Autonomy SME, Lead

Reston, VA · On-site

$112K - $257K/yr

... Engineering field Nice If You Have: * Experience working in military exercises and war games * Experience with autonomy frameworks such as Hivemind, PX4, ArduPilot, NVIDIA Isaac, or ROS2 * Experience ...

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All JobsNvidia Engineering JobsNvidia Engineering Jobs in Washington, DC

Nvidia Engineering information

See Washington, DC salary details

$52.7K

$166.3K

$197.1K

How much do nvidia engineering jobs pay per year?

As of Aug 16, 2026, the average yearly pay for nvidia engineering in Washington, DC is $166,342.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,900.00 and $195,900.00 per year, depending on experience, location, and employer.

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

To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.

What is an Nvidia engineer?

An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.

What types of projects do Nvidia engineers typically work on, and how is teamwork structured within the engineering department?

Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.

What are the most commonly searched types of Nvidia Engineering jobs in Washington, DC?

The most popular types of Nvidia Engineering jobs in Washington, DC are:

What are popular job titles related to Nvidia Engineering jobs in Washington, DC?

For Nvidia Engineering jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Nvidia Engineering jobs in Washington, DC look for?

The top searched job categories for Nvidia Engineering jobs in Washington, DC are:

Nvidia Engineering jobs near you
Infographic showing various Nvidia Engineering job openings in Washington, DC as of August 2026, with employment types broken down into 89% Full Time, 6% Part Time, 4% Contract, and 1% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $166,342 per year, or $80 per hour.

Senior AI Engineer

Via Logic LLC

Rockville, MD • On-site

$130 - $160/hr

Other

Posted 5 days ago

Job description

Join Leidos’ all‑star team supporting the Defense Intelligence Agency’s Enterprise Digital Modernization Accelerator initiative. Through training, teamwork, and exposure to challenging technical work, Leidos accelerates your career path.

As a Senior AI Engineer, you will
  • Support the development and operationalization of AI and agentic AI systems in production mission environments.
  • Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges and deliver innovative, production‑ready algorithms and platforms.
  • Apply cutting‑edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics.
  • Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast‑paced, engineering‑centric environment.
  • Enjoy flexible work arrangements, including remote and on‑site work in the National Capital Region (Rockville, MD and/or Alexandria, VA).
What You Bring
  • Bachelor’s, Master’s, or equivalent graduate degree in a quantitative or analytical field (Computer Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.). Additional/Relevant experience may be substituted for a degree.
  • 12+ years of experience in data science, analytics, or quantitative intelligence analysis, developing analytics and AI/ML solutions (4+ years with a Master’s).
  • Active Top Secret clearance and eligibility for TS/SCI with Polygraph.
  • Demonstrated experience collaborating with hybrid teams to research, build, and deploy complex, user‑friendly analytical platforms.
  • Track record of creative problem solving, active learning, and mission‑focused outcomes.
  • Experience with the following:
    • AI/ML production engineering
    • LLMOps / MLOps
    • RAG architectures
    • AI orchestration frameworks
    • Kubernetes‑based AI deployments
    • OpenAI‑compatible APIs
    • Python development
    • GPU inference optimization
Preferred Qualifications
  • Experience supporting military or intelligence community customers.
  • Familiarity with Azure/C2S, hardware platforms (CPUs, GPUs, FPGAs), and advanced analytical methodologies (social network analysis, supply chain analysis, NLP, classification algorithms, image processing).
  • Familiarity with the following technologies:
    • LangGraph
    • Semantic Kernel
    • vLLM
    • Ollama
    • Ray
    • NVIDIA GPU ecosystems
    • Vector databases
Commitment to Non‑Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.

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