Scientific Developer for Model Optimization
About The Position
Lynker Corporation is seeking a Scientific Developer for Model Optimization to support improved operational weather forecasting through scientific software development and high-performance computing. The role focuses on identifying and resolving performance bottlenecks in the UFS Weather Model with its integrated MPAS atmospheric dynamic core and coupled components. The developer will optimize code and builds, support heterogeneous and portable computing—especially CPU and GPU—and establish profiling and reproducible workflows for large parallel applications. The position also supports integration of optimized, accelerator-enabled, and profiling-enabled components into the UFS build system; ports and tests accelerated code on suitable hardware; investigates bit-for-bit reproducibility across CPU and GPU implementations; and contributes technical documentation. The developer collaborates with other teams, provides technical guidance and mentoring, and explores and validates GenAI/LLM use for improving code quality and development efficiency. The ideal candidate is local to the DC Metro area and works a hybrid schedule: two days per week in the College Park, Maryland office and three days per week from home. Lynker describes itself as an employee-owned professional, scientific, and technical services business with a team-oriented environment and opportunities for learning and career growth.
Requirements
- 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, 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 such as CUDA, OpenACC, OpenMP target offloading, Kokkos, RAJA, PyTorch, or JAX.
- Familiarity with profiling concepts and/or tools such as gprof, TAU, or Scalasca.
- Experience with Linux/Unix shell scripting and automation.
- Demonstrated proficiency with Git or similar code collaboration and management tools.
- Demonstrated ability to apply software engineering concepts and best practices.
Nice To Haves
- Demonstrated experience with build systems such as CMake, Meson, autotools, or make; strong proficiency in configurable scripting and automation is also acceptable.
- 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 tools such as ecFlow, Rocoto, or Cylc and package management tools such as Spack or pip in HPC environments.
- Familiarity with leveraging GenAI/LLM tools to optimize and assist software development workflows.
- Familiarity with continuous integration workflows and frameworks.
Responsibilities
- Identify and resolve performance bottlenecks in the UFS Weather Model with the integrated MPAS atmospheric dynamic core and coupled components.
- Identify model performance improvements through code optimization, build configuration, and heterogeneous and portable computing, particularly CPU and GPU computing.
- Implement runtime profiling for large parallel applications, including CPU and GPU performance, memory, cache, and disk I/O profiling.
- Develop configurable, reproducible frameworks and workflows for profiling and optimization.
- Enable integration of optimized, GPU/accelerator-enabled, and profiling-enabled components into the UFS build system, including compiler, package, profiling, and instrumentation configuration.
- Identify available computing hardware, and port and test accelerated code on appropriate systems while ensuring portability and reproducibility within acceptable tolerance.
- Investigate bit-for-bit reproducibility for CPU and GPU optimizations and propose and implement appropriate tests.
- Contribute strategic, technical, and other documentation concerning profiling, instrumentation, optimization, and GPU/portable programming.
- Collaborate with other teams to support models, forecast workflows, and other functions by delivering 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 GenAI/LLMs to improve code quality and development efficiency.
Benefits
- Comprehensive healthcare for the employee at no monthly cost, covering medical, prescription drug, dental, and vision.
- Personal Time Off (PTO) policy and paid holidays.
- Highly competitive compensation plan regularly calibrated against industry and location benchmarks.
- 401(k) retirement plan with company matching.
- Employee Stock Ownership Plan (ESOP).
- Flexible spending accounts.
- Employee assistance program (EAP).
- Short- and long-term disability insurance.
- Life and accident insurance.
- Tuition assistance, training, and workforce improvement reimbursement per year.
- Spot bonuses for exceptional performance.
- Annual Employee Recognition Awards with bonuses.
- Employee Referral Program.
- Free centralized, self-directed Learning Management System.
- Personalized career growth plans for every employee.
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What This Job Offers
Job Type
Full-time
