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Cuda Programming Jobs in Washington (NOW HIRING)

Jacobs

Mid-Level Linux Software Engineer

Chantilly, VA · On-site

... programming in CUDA for GPU accelerated applications • Familiarity with signal processing concepts • Knowledge and experience Jacobs is an Equal Opportunity/Affirmative Action Employer. All ...

GRVTY

DevSecOps - Platform Engineer

Reston, VA · On-site

They are seeking a DevSecOps - Platform Engineer to build and operate secure infrastructure for ... and CUDA enabled infrastructure for compute workloads. Company : GRVTY is a defense technology ...

Lockheed Martin

DevOps Engineer Staff

Fort George G Meade, MD · On-site

$58.75 - $80.50/hr

The GG DevOps SWE is in an extremely customer facing role leading multi faceted mission critical ... Configure and optimize GPU resources for performance-critical applications, utilizing CUDA or other ...

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How much do cuda programming jobs pay per hour?

As of Jun 22, 2026, the average hourly pay for cuda programming in Washington is $61.56, according to ZipRecruiter salary data. Most workers in this role earn between $49.81 and $71.88 per hour, depending on experience, location, and employer.

What is the difference between Cuda Programming vs GPU Developer?

AspectCuda ProgrammingGPU Developer
Required CredentialsKnowledge of CUDA, C/C++, parallel computingKnowledge of GPU architecture, CUDA, OpenCL, C/C++
Work EnvironmentHigh-performance computing, scientific research, AIGraphics, gaming, scientific visualization, AI
Industry UsageTech companies, research labs, AI firmsGaming, entertainment, tech, research

While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.

What are popular job titles related to Cuda Programming jobs in Washington? For Cuda Programming jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Cuda Programming jobs in Washington look for? The top searched job categories for Cuda Programming jobs in Washington are:
What cities in Washington are hiring for Cuda Programming jobs? Cities in Washington with the most Cuda Programming job openings:
Cuda Programming jobs near you
Infographic showing various Cuda Programming job openings in Washington as of June 2026, with employment types broken down into 74% Full Time, and 26% Contract. Highlights an 69% In-person, and 31% Remote job distribution, with an average salary of $128,052 per year, or $61.6 per hour.

AI Infrastructure & Full-Stack Engineer (Part-Time or Retainer - FT Flexibility) (Active TS/SCI Full

Catalyst Operations & Analytics

Vienna, VA • On-site

Contractor

Posted 20 days ago

Job description

Salary:

We're Hiring: AI Infrastructure & Full-Stack Engineer (Part-Time or Retainer FT Flexibility)

Catalyst is looking for a highly skilled engineer to support the design, deployment, and optimization of our on-premises AI infrastructure. This role can be part-time, on-retainer, or structured as an independent contractor, with flexibility to expand to full-time if needed.


What Youll Work On:

  • Designing and maintaining on-prem AI stacks GPU servers, local clusters, NAS storage
  • Building and managing Docker/Docker Compose environments
  • Optimizing model-inference pipelines for speed and reliability
  • Developing backend services and APIs for AI applications
  • Automating system setup and maintenance with Bash, Python, or PowerShell
  • Managing GPU drivers, CUDA, and dependency stacks
  • Implementing logging, metrics, and fault-tolerant distributed systems
  • Integrating AI systems with local networks (DNS, SSL/TLS, reverse proxy, firewall, auth)
  • Maintaining clear documentation and deployment procedures


Required Expertise:

  • Strong proficiency inPython,JavaScript, and full-stack development
  • Proven experience runningGPU-accelerated workloadsin Linux environments
  • Deep knowledge ofDocker, GPU runtime management, and multi-container orchestration
  • Linux server administration, security hardening, and user-permission management
  • Networking fundamentals (VLANs, NAT, DNS, reverse proxying)
  • System performance tuning (CPU/GPU/RAM)
  • Ability to read/debug code without IDE or internet access

Must hold an active TS/SCI Full Scope clearance.