CCS Global Tech is a rapidly growing Information Technology company with a diverse portfolio of technology products and services and a large network of industry partnerships. With over 22 years of being a successful business with a global talent pool and presence, CCS is a certified Microsoft Gold Partner and specializes in delivering expert Microsoft based solutions for technical and business needs. We have been recognized by Inc. 500 Magazine as one of the fastest growing small companies in the Unites States.
we are a Tier 1 vendor for the City and County of San Francisco for Cloud Services, Staffing Services and Training Services. For this multi-year opportunity with a diverse set of needs to address, we are currently focusing on establishing partnerships with individuals as well as companies who can help us enhance our overall service portfolio, cut lead times, and ultimately help us deliver successfully. We currently hold sizable Government accounts in the San Francisco bay area including City and County of San Francisco, San Mateo County, and Santa Clara County.
We take great pride in our global reach and local influence. Your experience alongside our highly skilled and talented internal team who guide you along the way, offers key insights into what helps you stand out in a competitive job market.
If you are a partner company, please submit resumes with contact information of your own W2 Consultants only. Submitted consultants are expected to have excellent communication skills.
Graphics Processing Unit (GPU) Engineer
Bethesda, Maryland
Location: Bethesda, MD
Salary: $131,300.00 - $190,000
Category: Systems Engineering
Travel Required: No
Remote Type: No
Clearance: TS/SCI Client is looking for a highly skilled Systems Engineer with deep expertise in operating systems, hardware, GPU, and high-speed networking. In this role, you will design, develop, and optimize GPU clusters that power enterprise AI for the mission customers.
This is a 100% on-site position.
Responsibilities: GPU Cluster Engineering: Design, configure, and maintain GPU Clusters. Collaborate with a multidisciplinary team to define and optimize architectures, ensuring they meet performance, power efficiency, and feature requirements.
Operating System Integration: Work closely with AI/ML engineers to ensure smooth GPU integration with Linux-based systems. Optimize GPU drivers for compatibility, reliability, and performance. Provide regular maintenance and updates.
Performance Optimization: Analyze GPU performance, identify bottlenecks, and develop strategies to improve efficiency across hardware and software layers.
Tooling and Automation: Build and maintain debugging tools, profiling utilities, and performance analysis software for Linux environments. Leverage scripting and configuration tools such as Bash, Python, Ansible, Puppet, and Salt.
Compliance & Documentation: Maintain technical documentation, architectural specifications, and Linux best practices. Support ATO (Authority to Operate) and ensure compliance with federal security standards.
You Bring Bachelor's or higher degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field with at least 12 years of related technical experience. Additional years of experience may be considered in lieu of a degree.
10+ years of relevant systems engineering experience
Experience in managing NVIDIA GPU data center platforms. (DGX, HGX, H200, H100, L4s).
Knowledge of enterprise server components (storage/network controllers, HBA, SSDs).
Strong expertise with Linux distributions. (RHEL, Ubuntu, Oracle, and Rocky).
Excellent problem-solving skills and the ability to collaborate within a team.
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.
ship is required due to the nature of the government contracts we support.
Preferred Qualifications Experience with Kubernetes cluster management and AI/ML workflow orchestration (Argo, Airflow, and Kubeflow).
Familiarity with GPU virtualization and cloud computing.
Experience with PrometheGrafana for monitoring.
Knowledge of distributed resource scheduling systems (Slurm (preferred), LSF, etc.).
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