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Assistant Cuda Jobs in Virginia (NOW HIRING)

Support containerized workloads (Docker, Podman, Singularity/Apptainer) * Assist with cluster ... Support GPU-enabled environments and CUDA-based workloads * Coordinate with engineering teams to ...

Support containerized workloads (Docker, Podman, Singularity/Apptainer) * Assist with cluster ... Support GPU-enabled environments and CUDA-based workloads * Coordinate with engineering teams to ...

HPC Systems Engineer

Charlottesville, VA · On-site

$150K - $200K/yr

Support containerized workloads (Docker, Podman, Singularity/Apptainer) * Assist with cluster ... Support GPU-enabled environments and CUDA-based workloads * Coordinate with engineering teams to ...

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

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Assistant Cuda information

What are the key skills and qualifications needed to thrive as an Assistant CUDA Developer, and why are they important?

To thrive as an Assistant CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and familiarity with GPU architectures, often backed by a degree in computer science or a related field. Proficiency with CUDA development tools, debugging utilities, and version control systems like Git is typically required. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for collaborating with teams and optimizing code. These skills ensure efficient development of high-performance applications and successful integration of GPU acceleration into software solutions.

What are Assistant Cuda roles and responsibilities?

An Assistant Cuda typically supports senior CUDA (Compute Unified Device Architecture) developers or teams working with NVIDIA’s parallel computing platform. Their responsibilities include assisting in developing, testing, and optimizing code written for GPUs to accelerate computing tasks, debugging CUDA applications, and maintaining documentation. They may also handle routine tasks such as performance benchmarking, code reviews, and collaborating with other team members to implement efficient GPU solutions. This role is crucial in organizations that rely on high-performance computing, scientific simulations, or AI workloads.

What is the difference between Assistant Cuda vs Assistant Data Analyst?

AspectAssistant CudaAssistant Data Analyst
Required CredentialsTypically a relevant degree in computer science or related fieldOften a degree in data science, statistics, or related field
Work EnvironmentTech companies, software development teams, AI projectsBusiness, finance, marketing, or research departments
Employer & Industry UsageUsed in tech and AI industries for supporting CUDA programming tasksCommon in data-driven industries for data processing and analysis

Assistant Cuda and Assistant Data Analyst roles share some technical background but differ mainly in focus. Assistant Cuda primarily supports GPU programming and AI development, while Assistant Data Analyst focuses on data interpretation and reporting. Both roles require relevant technical skills and are found in industries leveraging data and technology, but their daily tasks and industry applications vary significantly.

What are some common challenges faced by Assistant CUDA developers when optimizing code for GPU performance?

Assistant CUDA developers often encounter challenges such as managing memory efficiently between the host and device, ensuring proper kernel parallelization, and avoiding thread divergence. Balancing occupancy and resource usage can also be tricky, as it requires a deep understanding of how CUDA schedules and executes threads. Collaborating closely with data scientists and other engineers is essential to identify performance bottlenecks and implement effective optimizations.
What are the most commonly searched types of Cuda jobs in Virginia? The most popular types of Cuda jobs in Virginia are:
What cities in Virginia are hiring for Assistant Cuda jobs? Cities in Virginia with the most Assistant Cuda job openings:

HPC Systems Engineer

teKnoluxion

Charlottesville, VA

$150K - $200K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago


Job description

OverviewHPC Systems EngineerLocation: Charlottesville, VA

Clearance Required:  Active TS (SCI eligibility) 

At Bcore, our strength comes from how we deliver impact to the mission. Whether it's architecting critical IT solutions, producing actionable intelligence, or developing cutting edge technology, we succeed because of the expertise, collaboration, and agility of our teams. Our Mission Services division combines enterprise IT, cloud solutions, DevSecOps, systems engineering, software development, and operational support. Bcore accelerates decisive advantage for warfighters and intelligence professionals by fusing human insight, rapid-fire engineering, precision-measured outcomes, and relentless grit into mission-ready solutions. 

Do you want to join a team that is building tailored technical solutions to modernize our government's mission and our client's business?  Do you have a desire to change how people work?  Are you interested in helping to protect our nation's cyber interests? Join our growing team supporting the Army customer's mission as an HPC Systems Engineer.

ResponsibilitiesWhat you get to do every day:
  • Build, configure, and maintain secure HPC clusters for simulations, scientific computing, and GPU workloads
  • Collaborate with infrastructure teams on cluster platforms, including schedulers, provisioning systems, high-speed interconnects, and distributed nodes
  • Configure and manage job schedulers (Slurm, PBS) with queue setup, resource policies, and job optimization
  • Support containerized workloads (Docker, Podman, Singularity/Apptainer)
  • Assist with cluster provisioning, node management, and initial build-out, including scheduler configuration and validation
  • Troubleshoot hardware, OS, scheduler, networking, and high-performance interconnect issues (e.g., InfiniBand)
  • Integrate compute nodes and hardware into clusters
  • Develop automation and operational tools using Bash, Python, or similar scripting
  • Support authentication and access control via LDAP or Kerberos
  • Analyze performance and identify bottlenecks across compute, storage, and network layers for distributed workloads (MPI/OpenMP)
  • Support GPU-enabled environments and CUDA-based workloads
  • Coordinate with engineering teams to improve cluster performance, stability, and scalability
  • Maintain documentation for configurations, procedures, and troubleshooting
  • Provide technical guidance on HPC best practices for mission workloads
Qualifications

Clearance Required: Active TS clearance (with SCI Eligibility) and eligibility to obtain CI Poly **We are not able to upgrade or sponsor clearances**

Certification Required: Ability to obtain DoD 8140 (8570) IAT Level II certification

Education/Experience:

  • Requires Bachelor's degree in Engineering, Computer Science, or related STEM field (experience in lieu of degree)
  • 6+ years of experience administering Linux based systems in enterprise, research computing, or distributed compute environments, including configuration and troubleshooting of multi-node systems.
Required Skills:
  • Experience supporting distributed compute environments with workload schedulers (e.g., Slurm, PBS, Torque, Grid Engine)
  • Experience supporting multi-node compute environments or HPC clusters
  • Professional experience administering Linux systems via CLI (RHEL derivatives preferred)
  • Experience with scripting and automation (Bash, Python, or similar)
  • Experience troubleshooting server hardware, OS, and distributed computing systems
  • Familiarity with cluster networking and high-speed interconnects
  • Experience diagnosing performance issues across compute, networking, and storage layers
  • Strong troubleshooting and documentation skills

What is ideal?

  • Experience administering multi-node HPC clusters and supporting distributed workloads
  • Knowledge of parallel file systems (e.g., Lustre, BeeGFS, GPFS)
  • Experience with parallel computing frameworks (MPI, OpenMP)
  • Experience with configuration management tools (Ansible, Puppet)
  • Experience supporting GPU-enabled environments and CUDA workloads
  • Familiarity with hybrid HPC architectures (on-prem + cloud, e.g., AWS)
  • Experience supporting HPC systems in research, lab, or mission environments
  • Experience working in DoD or IC environments preferred
What you can expect from us
  • Recognizing great achievements do not go unnoticed by Bcore through service anniversaries, spot awards, and employee referral bonuses
  • You'll join a growing organization of passionate, top-shelf, IT engineering professionals with extensive experience in actively developing the technology revolution in the Intelligence community
  • The expected salary range within the Washington, DC metropolitan area is: $150,000-$200,200.00. Final compensation is unique to each individual and will be determined based on factors such as experience, education, geographic location, and contractual requirements. This is not a guarantee.
  • Benefits include Health/Dental/Vision, 401(k) match, Paid Time Off, STD/LTD/Life Insurance/Voluntary Life Insurance, Stipends, Referral Bonuses, and more.
BCore is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.Employment Type: FULL_TIME