HPC Consultant: Performance & Application Support (Hybrid)

Los Alamos National Laboratory; Los Alamos (NM); Hybrid; USD 106,000 - 216,000; Full time

Benefits offered by this job

Medical insurance (PPO or HDHP)

Dental and vision insurance

Tuition assistance

Flexible schedules and PTO

Job summary

Los Alamos National Laboratory (LANL) seeks an HPC Engineer to support scientists and engineers in an external-candidates-only role. You will guide users, document best practices, and help optimize large-scale simulations and AI workloads across CPU/GPU platforms.

Responsibilities include developing guides, training materials, and troubleshooting performance issues while collaborating with system admins and developers. Hybrid work in Los Alamos area is available.

Qualifications

• Bachelor’s degree in CS/CE or related field with relevant HPC experience.
• Strong programming skills in C/C++, Fortran, and Python.
• Experience with Linux-based HPC environments and parallel workloads.
• Familiarity with MPI, OpenMP, CUDA, and GPU-accelerated apps.
• Ability to communicate effectively with scientists and engineers.

Responsibilities

• Provide expert guidance to scientists and engineers to optimize HPC workflows.
• Develop user guides, best practices, and training materials for HPC users.
• Collaborate with system administrators to improve performance and resource utilization.
• Troubleshoot complex parallel apps and assist with porting efforts.
• Represent LANL HPC Consulting at workshops and technical meetings.
• Support containerized workflows and HPC software stacks across platforms.

Skills

Communication skills

Linux

HPC environments

Programming (C/C++/Fortran/Python)

MPI/OpenMP/CUDA

Education

Bachelor's in Computer Science/Engineering or related field

Tools

NVIDIA HPC SDK

Intel/LLVM/GNU compilers

Spack/Environment Modules

CUDA

Job description

Los Alamos National Laboratory (LANL) seeks an HPC Engineer to support scientists and engineers in an external-candidates-only role. You will guide users, document best practices, and help optimize large-scale simulations and AI workloads across CPU/GPU platforms.

Responsibilities include developing guides, training materials, and troubleshooting performance issues while collaborating with system admins and developers. Hybrid work in Los Alamos area is available.