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Contract Gpu Jobs (NOW HIRING)

Machine Intelligence Technologies, LLC

WI · On-site

GPU Bare MetalRequired Skills * Proven ability to orchestrate bare metal linux systems at scale ... contract #J-18808-Ljbffr

Machine Intelligence Technologies, LLC

GPU Bare MetalRequired Skills * Proven ability to orchestrate bare metal linux systems at scale ... contract #J-18808-Ljbffr

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Contract Gpu information

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$106K

$139K

How much do contract gpu jobs pay per year?

As of Sep 13, 2026, the average yearly pay for contract gpu in the United States is $106,034.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,000.00 and $119,000.00 per year, depending on experience, location, and employer.

What is a contract GPU?

Contract GPU jobs are temporary or project-based positions that require expertise in graphics processing units (GPUs). These jobs often involve developing, optimizing, or deploying GPU-accelerated applications, such as in machine learning, scientific computing, game development, or rendering. Contract workers may be hired by companies for specific tasks that need specialized knowledge in GPU programming using tools like CUDA or OpenCL. These roles can be remote or on-site and typically last for the duration of a particular project or set timeframe.

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

To thrive as a Contract GPU Engineer, you need a strong background in computer science, GPU architecture, and parallel programming, often supported by a degree in a relevant field and prior experience with graphics hardware. Familiarity with tools and frameworks such as CUDA, OpenCL, DirectX, Vulkan, and performance profiling utilities is typically required. Excellent problem-solving, time management, and communication skills are crucial for collaborating with diverse teams and meeting project deadlines. These competencies ensure efficient development, optimization, and deployment of GPU-accelerated solutions in dynamic contract environments.

What are some common challenges faced by professionals working in contract GPU roles, and how can they address them?

Professionals in contract GPU roles often encounter challenges such as rapidly evolving hardware and software standards, tight project timelines, and the need to quickly adapt to different team environments. Staying updated with the latest GPU technologies and frameworks is essential, as is developing strong communication skills to collaborate effectively with full-time team members and stakeholders. To address these challenges, leveraging online resources, participating in relevant forums, and proactively seeking feedback can help contract GPU specialists deliver high-quality results and integrate smoothly into diverse project teams.

What is the difference between Contract Gpu vs Contract Data Scientist?

AspectContract GpuContract Data Scientist
Required CredentialsGPU certifications, technical skills in GPU programmingStatistics, programming, data analysis certifications
Work EnvironmentTech companies, research labs, AI firmsTech firms, finance, healthcare, consulting
Employer & Industry UsageAI development, machine learning projectsData analysis, predictive modeling, business insights

Contract Gpu roles focus on GPU hardware and software expertise for AI and machine learning projects, while Contract Data Scientist roles emphasize data analysis, statistical modeling, and insights. Both are in tech-driven industries but serve different technical functions.

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What states have the most Contract Gpu jobs?

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Contract Gpu jobs near you
Infographic showing various Contract Gpu job openings in the United States as of September 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 100% In-person job distribution, with an average salary of $106,034 per year, or $51 per hour.

Systems Engineer - HPC & GPU Infrastructure

Bethesda, MD • On-site

Leidos
IT Services • 10K+ employees
Learn more about Leidosexternal

$87K - $157K/yr

Full-time

Re-posted 5 days ago

Leidos rating

8.3

Company rating: 8.3 out of 10

Based on 154 frontline employees who took The Breakroom Quiz

Job description

Leidos is looking for a mid-career Systems Engineer (Mid-Career) - HPC & GPU Infrastructure with a deep understanding of operating systems, hardware, Kubernetes, and NVIDIA GPU products. As a Systems Engineer (Mid-Career) - HPC & GPU Infrastructure, you will play a pivotal role in designing, developing, and optimizing GPU clusters for the IC community customers.
This is a 100% on-site position. All work must be performed at the customer site in Bethesda at the Intelligence Community Campus.
Responsibilities:
  • HPC and GPU environment engineering: Contribute to the installation and maintenance of GPU and HPC hardware on-prem and in the cloud, providing insights into hardware performance to ensure efficient interaction with software components.
  • Performance Optimization: Analyze HPC/GPU cluster performance, identify bottlenecks, and develop strategies to enhance performance across various applications in Linux, addressing both hardware and software considerations. Regularly monitor and improve performance.
  • HPC/GPU tooling: Install and configure HPC/GPU job scheduling and workload management platforms such as Slurm , PBS , Apache Airflow , Kubernetes
  • Power Efficiency: Work on power management techniques to optimize GPU power consumption, ensuring efficient operation on both mobile and desktop Linux platforms. Continuously assess and enhance power efficiency strategies.
  • Testing and Validation: Design and execute tests to validate GPU performance and functionality on Linux, including stress testing, benchmarking, and debugging to ensure robust operation. Maintain and expand the testing suite.
  • Documentation: Maintain comprehensive technical documentation, including architectural specifications, code documentation, and Linux-specific best practices for GPU development. Keep documentation up to date with changes and improvements.
  • Industry Insight: Stay updated on the latest trends, innovations, and competitive landscapes within the GPU industry, contributing to research efforts and proposing Linux-specific approaches to GPU design and optimization. Share regular updates and insights with the team.

You Bring
  • Bachelor's or higher degree in Computer Science, Electrical Engineering, or a related field. Additional years of experience may be considered in lieu of a degree.
  • 4+ years of relevant systems engineering experience
  • Expertise in operating system integration for Linux.
  • Strong understanding of computer hardware architecture, particularly as it relates to Linux systems.
  • Knowledge of parallel computing, graphics algorithms, and real-time rendering in Linux environments.
  • Excellent problem-solving skills and the ability to collaborate within a team.
  • Strong communication skills for conveying technical information in a Linux context.
  • Proficiency with scripting languages such as Python or BASH.
  • Proficiency with automation tools such Ansible, Puppet, Salt, Terraform, etc.
  • Candidate must, at a minimum, meet DoD 8570.11- IAT Level II certification requirements (currently Security+ CE, CCNA-Security, GICSP, GSEC, or SSCP along with an appropriate computing environment (CE) certification). An IAT Level III certification would also be acceptable (CASP+, CCNP Security, CISA, CISSP, GCED, GCIH, CCSP).

Clearance
  • Active TS/SCI clearance with Polygraph required OR active TS/SCI and willingness to obtain and maintain a Poly.
  • US Citizenship is required due to the nature of the government contracts we support.

Preferred Qualifications
  • Knowledge of GPU virtualization, cloud computing, and emerging Linux-based technologies in the field.
  • Experience with container technologies (Docker, Kubernetes)
  • Experience with Prometheus/Grafana for monitoring
  • Knowledge of distributed resource scheduling systems
  • Understanding data center networking hardware and cabling concepts.
  • Understanding of networking technologies such as DHCP, DNS, TCP/IP, VLANs, HSRP, and SNMP.
  • Knowledge of data center networking security principles Firewall ACLs, IPS/IDS, and Policy Based Routing.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.
Original Posting:
September 4, 2026
For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $87,100.00 - $157,450.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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About Leidos

Sourced by ZipRecruiter

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers' success. We empower our teams, contribute to our communities, and operate sustainable practices. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Reston, VA, US

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