Scientific Developer for Model Optimization

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

Benefits offered by this job

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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

Scientific Developer for Model Optimization

US-MD-College Park

Job ID: 2026-1727

Type: Full-Time

# of Openings: 1

College Park, MD

Overview

Lynker Corporation is a leading provider of innovative solutions in weather and climate science. With a commitment to excellence and a passion for innovation, Lynker leverages cutting-edge technologies and scientific expertise to support the creation and delivery of improved operational weather forecasts.

The ideal Scientific Software Developer for MPAS Infrastructure will be local to the DC Metro area, and be able to work a hybrid schedule, working 2 days per week in office out of the College Park, MD location, and working from home the remaining 3 days of the week.

Responsibilities

Duties of the Scientific Developer for Model Optimization will include the following:

• 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.

Qualifications

The Scientific Developer for Model Optimization selected should have the following:

• 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.
• Familiarity with GPU/heterogeneous programming and/or portability frameworks (e.g., CUDA, OpenACC, OpenMP target offloading, Kokkos, RAJA, PyTorch, JAX).
• Familiarity with profiling concepts and/or tools (e.g., gprof, TAU, Scalasca)
• Experience with Linux/Unix shell scripting and automation.
• Demonstrated experience with build systems (e.g., CMake, Meson, autotools, make) is strongly preferred, however, strong proficiency in configurable scripting and automation is acceptable.
• Demonstrated proficiency with Git or similar tools for code collaboration and management.
• Demonstrated ability to apply the concepts of software engineering and best practices.

The Ideal Scientific Developer for Model Optimization will have the following:

• Ph.D. in a quantitative field with research computing experience.
• Direct experience with the Unified Forecast System (UFS), MPAS, or other atmospheric modeling systems. Familiarity with NWP forecast workflows is beneficial.
• Experience with workflow (ecFlow, Rocoto, Cylc) and package (Spack, pip) management tools in HPC environments.
• Familiarity with leveraging GenAI/LLM tools to optimize and assist software development workflows.
• Familiarity with continuous integration (CI) workflows and frameworks.

About Lynker

Lynker is a growing, employee owned business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.

We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities – creatively and effectively.

Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled professionals who embrace sound science and creative solutions. Lynker's benefits include the following:

• Personalized career growth plans for every employee

Lynker is an E-Verify employer.

Lynker is an equal opportunity employer and makes all employment decisions based on merit, qualifications, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other legally protected status under federal, state, or local laws.

Equal employment opportunity, including veterans and individuals with disabilities.

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