Apply on Employer Site

Xcelerate Solutions · 3 days ago

Graphic Processing Unit (GPU) Engineer - TS/SCI

Bethesda, MD

Full-time

Onsite

Senior Level, Lead/Staff

10+ years exp

Xcelerate Solutions is looking for a highly skilled Graphics Processing Unit (GPU) Engineer with expertise in operating systems and hardware. The role involves designing, developing, and optimizing GPUs for various applications, focusing on seamless integration with Linux-based systems.

B2BRoboticsSoftware

Growth Opportunities

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Collaborate with a multidisciplinary team to define, develop, and optimize GPU architectures, ensuring they meet stringent performance, power efficiency, and feature requirements

Work closely with operating system developers to ensure smooth GPU integration with Linux-based systems

Contribute to the design and development of GPU hardware, providing insights into hardware architecture to ensure efficient interaction with software components

Develop and optimize applications using CUDA or OpenCL, harnessing the full potential of GPU hardware for parallel processing, high-performance computing, and machine learning on Linux platforms

Analyze GPU performance, identify bottlenecks, and develop strategies to enhance performance across various applications in Linux, addressing both hardware and software considerations

Create and maintain debugging tools, profiling utilities, and performance analysis software tailored for Linux systems to facilitate efficient GPU development and troubleshooting

Work on power management techniques to optimize GPU power consumption, ensuring efficient operation on both mobile and desktop Linux platforms

Design and execute tests to validate GPU performance and functionality on Linux, including stress testing, benchmarking, and debugging to ensure robust operation

Maintain comprehensive technical documentation, including architectural specifications, code documentation, and Linux-specific best practices for GPU development

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

Qualification

GPU architecture designLinux operating systemsCUDA programmingGPU performance optimizationHardware architectureParallel computingGPU debugging toolsScripting languagesAutomation toolsMachine learning frameworksContainer technologiesMonitoring toolsDeep learning frameworksProblem-solving skillsCommunication skills

Required

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

10+ years of relevant systems engineering experience

Proven experience in GPU architecture design, and GPU performance optimization

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

Familiarity with GPU debugging tools and profiling software for Linux

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)

Preferred

Published research or contributions in the GPU industry, especially related to Linux

Experience with machine learning and neural network frameworks on GPUs in Linux

Knowledge of GPU virtualization, cloud computing, and emerging Linux-based technologies in the field

Proficiency in programming languages such as GPU-specific languages

Experience with container technologies (Docker, Kubernetes)

Experience with Prometheus/Grafana for monitoring

Knowledge of distributed resource scheduling systems [Slurm (preferred), LSF, etc.]

Familiarity with CUDA and managing GPU-accelerated computing systems

Basic knowledge of deep learning frameworks and algorithms

Benefits

Pay Transparency Notice: Xcelerate Solutions will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.