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Parallel Works

HPC and AI workload orchestration platform

Senior HPC Applications Engineer

System AdministrationConfirmed live in the last 24 hours
Full-timeRemote in USA$115k - $140kRemote

About the Job

Requirements

  • At least 10 years supporting scientific or AI application users on Linux high-performance computing systems.
  • Build complex software from source on RHEL-family and Debian or Ubuntu systems, including compilers, MPI, CMake, autotools, and dependency management.
  • Run Spack or EasyBuild and Lmod in production.
  • Have experience with multi-node GPU workloads from the platform side and distinguish framework problems from environment problems.
  • Work with site-provided software stacks on on-premises systems and cloud images where the full stack is controlled.
  • Have working knowledge of at least one application domain: weather and climate, computational fluid dynamics, molecular and materials science, or structural analysis.
  • Be a United States citizen and eligible for a Secret clearance; an active clearance is helpful but not required.
  • The posting says applicants do not need every listed item and encourages applying with most of them.

Responsibilities

  • Own the software stack and user experience on the company's platforms, serving as the escalation point for build failures, jobs that fail during multi-node runs, and jobs with below-expected throughput.
  • Compile and package MPI implementations, compilers, and scientific libraries, delivering them through Spack or EasyBuild with navigable Lmod module trees.
  • Install requested AI and machine-learning frameworks; enable multi-node GPU launches; diagnose NCCL and collective behavior, container and driver mismatches, storage throughput, and node faults during runs.
  • Run scaling studies and profile workloads with Nsight, VTune, TAU, HPCToolkit, or Score-P; pass findings to the systems team when the fix belongs in the fabric or filesystem.
  • Port customer codes to new GPU architectures and venues, using containers when preferable to rebuilding against each site's modules.
  • Triage tickets, diagnose failed jobs to root cause, and close them with a written explanation.
  • Create user guides, hold office hours, and train user communities, including through formal Government training events.
  • Work directly with users to understand their goals and carry problems from initial report through resolution.

Desired Qualifications

  • Prior user-facing experience at a Government supercomputing center, national laboratory, or university HPC center.
  • Depth with profiling and debugging tools, including a GPU profiler, a CPU profiler, gdb, and MPI tooling.
  • Hands-on distributed training or inference using PyTorch DDP or FSDP, DeepSpeed, Megatron-style frameworks, JAX, vLLM, or TensorRT-LLM.
  • Experience supporting Jupyter, remote visualization, or virtual desktops for research users.

About the Company

Parallel Works

HPC and AI workload orchestration platform

Parallel Works provides ACTIVATE, a computing control plane that orchestrates HPC and AI workloads across on-premises, cloud, and hybrid environments. It lets teams provision, manage, and share compute resources for simulations, data analytics, and other compute-heavy tasks through a central interface, coordinating job scheduling, data movement, and resource provisioning across multi-cloud infrastructure. Its cross-environment orchestration capability and its Argonne National Laboratory origins differentiate it from competitors by focusing on broad access to HPC and AI capabilities for scientific research and engineering. The goal is to simplify complex computational workflows so organizations can focus on research and development rather than IT infrastructure.

Company size
11-50
Company stage
Seed
Total funding
$870K
Headquarters
Chicago, IL
Founded
2015

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