Hybrid HPC Scientist - Model Optimization & Profiling

Lynker Technologies; College Park (MD); Hybrid; USD 120,000 - 180,000; Full time

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Job summary

Lynker Technologies is seeking a Scientific Developer for Model Optimization in College Park, MD, to advance weather model performance using MPAS/UFS, CPUs/GPUs, and portable computing techniques. The role emphasizes profiling, optimization, and reproducibility across large-scale parallel systems.

You will collaborate with multiple teams, mentor colleagues, and explore GenAI/LabM models to improve code quality and development efficiency in a hybrid work setup.

Qualifications

• Bachelor's or Master's degree in meteorology, atmospheric science, physical sciences, mathematics, computer science, software engineering, scientific computing, or a closely related field with demonstrated numerical modeling or closely related scientific computing experience.
• Demonstrated experience in high-performance computing (HPC), software optimization, and building, running, debugging, and profiling large-scale parallel applications.
• Proficiency in C, C++, and/or Fortran, as well as MPI.

Responsibilities

• Identify and resolve performance bottlenecks in the UFS Weather Model with the newly integrated MPAS atmospheric dynamic core and coupled components.
• Identify opportunities for model performance improvement, including through code optimization, build configuration, and heterogeneous and portable computing, especially with CPU and GPU.
• Implement code run-time profiling for large parallel applications, including profiling of CPU & GPU performance, memory usage, cache usage, and disk I/O.
• Develop configurable, reproducible frameworks/workflows for doing so.
• Enable the integration of optimized, GPU/accelerator-enabled and profiling-enabled components into the UFS build system, including configuration of compilers, packages, and profiling/instrumentation.
• Identify available computing hardware resources and port and test accelerated code on appropriate systems, ensuring robust portability and reproducibility within acceptable tolerance.
• Investigate bit-for-bit reproducibility in the context of CPU and GPU optimizations, and propose and implement appropriate reproducibility tests.
• Contribute to strategic, technical, and other documentation regarding profiling/instrumentation, optimization, and GPU/portable programming .
• Collaborate with other teams to support models, forecast workflows, and other functions through the delivery of optimized code and profiling/instrumentation frameworks. Provide technical guidance and mentoring to colleagues on profiling/instrumentation, optimization, and GPU/portable code development.
• Explore and validate the use of Generative AI (GenAI)/Large Language Models (LLMs) to improve the quality of code and the efficiency of code development process.

Skills

HPC experience

C/C++/Fortran

MPI

GPU/heterogeneous programming

Profiling tools

Linux/Unix scripting

Build systems

Git

Software engineering principles

Education

Bachelor's or Master's degree in meteorology, atmospheric science, physical sciences, mathematics, computer science, software engineering, scientific computing

Ph.D. in a quantitative field (preferred)

Tools

CUDA

OpenACC

OpenMP target offloading

Kokkos

RAJA

PyTorch

JAX

gprof

TAU

Scalasca

CMake

Meson

autotools

make

ecFlow

Rocoto

Cylc

Spack

pip

Job description

Lynker Technologies is seeking a Scientific Developer for Model Optimization in College Park, MD, to advance weather model performance using MPAS/UFS, CPUs/GPUs, and portable computing techniques. The role emphasizes profiling, optimization, and reproducibility across large-scale parallel systems.

You will collaborate with multiple teams, mentor colleagues, and explore GenAI/LabM models to improve code quality and development efficiency in a hybrid work setup.