Staff HPC Applications Engineer — Accelerate Apps at Scale (Hybrid/Remote)

NextSilicon; Minneapolis (MN); Hybrid; USD 120,000 - 170,000; Full time

Job summary

NextSilicon is seeking a Staff Applications Engineer to move HPC applications onto new platforms and measure gains on node and scale. You will help shape software features for a dataflow architecture and work across scientific fields.

The role requires strong MPI/OpenMP, C/C++, Fortran, and PyTorch experience, with travel as needed. Hybrid in Austin or Minneapolis; remote for exceptional candidates.

Qualifications

• BS in engineering with significant focus on scientific computing.
• MS or PhD with relevant specialization is a plus.
• Strong parallel programming experience using MPI and OpenMP required.
• Hands-on with HPC application domains.
• Hands-on with AI/ML frameworks such as PyTorch.
• Proficiency in C/C++ and/or Fortran.
• Ability to measure and profile HPC performance at node and scale.
• Willingness to travel as necessary.
• US citizenship with eligibility to visit US government facilities.

Responsibilities

• Profile and identify bottlenecks of HPC applications on different architectures.
• Develop algorithms and software to accelerate applications on a novel dataflow architecture.
• Translate application requirements into software features and hardware requirements.
• Develop performance models for future hardware architectures.

Skills

MPI

OpenMP

C/C++

Fortran

HPC applications

AI/ML (PyTorch)

travel willingness

US citizenship

Education

BS in engineering with scientific computing focus

MS or PhD (plus)

Tools

PyTorch

Job description

NextSilicon is seeking a Staff Applications Engineer to move HPC applications onto new platforms and measure gains on node and scale. You will help shape software features for a dataflow architecture and work across scientific fields.

The role requires strong MPI/OpenMP, C/C++, Fortran, and PyTorch experience, with travel as needed. Hybrid in Austin or Minneapolis; remote for exceptional candidates.