Senior HPC Applications Engineer
Parallel Works
| Company | Parallel Works |
| Category | Uncategorised |
| Location | Chicago |
| Remote | Remote |
| Employment | Full-time |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 1 Aug 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (workable) |
Description
About Parallel Works Parallel Works builds and operates ACTIVATE, a control plane for high performance computing and AI. Our customers run large scientific and AI workloads across their own on-premises clusters, Government and commercial cloud, and commercial GPU providers, and ACTIVATE gives them one way in to all of it. The high security boundary is authorized at Impact Level 5, with FIPS validated cryptography and STIG hardening throughout. The work reaches most fields that depend on computing at scale: weather and climate forecasting, defense and intelligence programs, aerospace and structural analysis, molecular and materials science, energy, and AI research. A quarter here can include standing up a GPU cluster for one of those communities, federating a laboratory's existing on-premises system with burst capacity it did not have before, and getting a domain code written decades ago to run on current hardware. Customer success sets our priorities. We are a small engineering company, so engineers here work directly with the people using the systems and carry a problem from the first report through to the fix. This is what we call mission engineering: understanding what a customer is trying to accomplish and why the computing matters to it. About the role Parallel Works is hiring a Senior HPC Applications Engineer to own the software stack and the user experience on our platforms. Our users are weather modelers, computational chemists, aerospace engineers, and AI researchers. The role is the escalation point for build failures, jobs that die partway through a multi-node run, and jobs running below expected throughput. The scope covers both long-lived domain codes and current AI workloads, since customers run both on the same clusters. Users also move between on-premises systems, cloud, and commercial GPU providers, so a large part of the job is making an application behave the same across different compilers, site modules, MPI builds, and filesystems. Expect to spend a good share of the week talking to users. What you will do Software stack: compile and package MPI implementations (OpenMPI, MPICH, Intel MPI, HPC-X), compilers (GCC, Intel oneAPI, NVHPC), and scientific libraries, delivered through Spack or EasyBuild with Lmod module trees users can navigate. Enable AI and ML workloads: install the frameworks customers ask for, get multi-node GPU launch working, and diagnose what sits below the framework: NCCL and collective behavior, container and driver mismatches, storage throughput, node faults mid-run. Customers drive their own toolchain choices. Performance work: run scaling studies, profile with Nsight, VTune, TAU, HPCToolkit, or Score-P, and hand the finding to the systems team when the fix belongs in the fabric or the filesystem. Portability: get customer codes running on new GPU architectures and new venues, using containers where that beats rebuilding against each site's modules. User support: triage tickets, diagnose failed jobs to a root cause, and close them with a written explanation. Documentation and training: user guides, office hours, and training for user communities, including formal Government training events.
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