GPU Engineer
Vector is seeking a Linux Server GPU Engineer position to support the National Media Exploitation Center. This role requires an individual that has technical experience of administering servers within a physical and virtual environment. This individual should be detail oriented in order to capture customer inquiries appropriately. This role is responsible for interacting with administrators to handle service inquiries and problems. Duties include examining customer problems and implementing appropriate corrective action to initiate a repair or return to service. This role analyzes recurring problems and initiates solutions for preventing reoccurrence and analyzes existing infrastructure for tuning/performance enhancements. The individual will provide systems and software operations and maintenance support in a large, multi-enclave enterprise environment. This individual will work in a team environment to ensure mission needs are met and ensure functionality of capabilities of customers. Individuals in this role may be required to perform technical software configuration, rebooting, and other remedial actions on customer servers. The Customer utilizes an Agile Framework to plan and successfully complete all initiatives. The work location is in Bethesda at the Intelligence Community Campus.
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. Optimize GPU drivers for compatibility, performance, and reliability in a Linux environment.
- 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.
Minimum Requirement:
- 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.
- Effective 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 Qualification:
- 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
Vector Talent Resources is an Equal Opportunity/Affirmative Action employer. All qualified candidates will receive consideration for employment without regard to disability, protected veteran status, race, color, religious creed, national origin, citizenship, marital status, sex, sexual orientation/gender identity, age or genetic information.
GPU Engineer
Vector is seeking a Linux Server GPU Engineer position to support the National Media Exploitation Center. This role requires an individual that has technical experience of administering servers within a physical and virtual environment. This individual should be detail oriented in order to capture customer inquiries appropriately. This role is responsible for interacting with administrators to handle service inquiries and problems. Duties include examining customer problems and implementing appropriate corrective action to initiate a repair or return to service. This role analyzes recurring problems and initiates solutions for preventing reoccurrence and analyzes existing infrastructure for tuning/performance enhancements. The individual will provide systems and software operations and maintenance support in a large, multi-enclave enterprise environment. This individual will work in a team environment to ensure mission needs are met and ensure functionality of capabilities of customers. Individuals in this role may be required to perform technical software configuration, rebooting, and other remedial actions on customer servers. The Customer utilizes an Agile Framework to plan and successfully complete all initiatives. The work location is in Bethesda at the Intelligence Community Campus.
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. Optimize GPU drivers for compatibility, performance, and reliability in a Linux environment.
- 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.
Minimum Requirement:
- 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.
- Effective 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 Qualification:
- 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
Vector Talent Resources is an Equal Opportunity/Affirmative Action employer. All qualified candidates will receive consideration for employment without regard to disability, protected veteran status, race, color, religious creed, national origin, citizenship, marital status, sex, sexual orientation/gender identity, age or genetic information.
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