Research Software Engineer
Team: [C]worthy
Location: Boulder, CO
Commitment: Full Time
Workplace Type: onsite
Salary:
Key Responsibilities
- Design, build, & maintain C-Star software components alongside a multidisciplinary team.
- Quickly generate working software prototypes to address emerging needs, and later harden those prototypes into production-grade software.
- Independently execute on medium-sized projects, keeping a focus on high-level goals while maintaining flexibility to diagnose and solve problems as they arise.
- Assist fellow developers via code reviews, design discussions, and testing.
- Support internal and external users via issue review, troubleshooting, tutorials, requirement-gathering, and documentation.
Minimum Qualifications
- Bachelor’s, Master’s, Doctorate degree, or equivalent work experience in a technical field (e.g., oceanography, atmospheric science, physical science, computer science)
- Excellent problem-solving and critical-thinking skills; ability to understand both scientific and software systems, and tackle abstract problems in the overlap between them
- 3+ years of experience writing clean, maintainable, object-oriented software in Python
- Experience working with multi-dimensional scientific datasets in Python (e.g., netcdf/zarr formats and Pangeo libraries, particularly xarray, numpy, and scipy)
- Experience working in interdisciplinary teams and translating scientific requirements into software specifications
Preferred Qualifications
- Exposure or experience building and running gridded numerical models (especially ocean models)
- Experience with HPC/supercomputer environments (SLURM, MPI, performant file systems)
- Experience with a workflow management package such as Prefect or Airflow
- Scientific background in physical or biogeochemical oceanography
- Exposure to agile/scrum methodologies; demonstrated ability to focus on objectives and iterate towards solutions
- Expertise in TB/PB-scale data engineering
- Ability to read and debug FORTRAN
- Experience with containerization frameworks such as Apptainer/Singularity or Podman/Docker
- Knowledge of data versioning, logging, and audit trails
- Experience with performant numerical Python techniques and libraries, such as Dask, Numba, and asyncio
- Experience working with cloud-based storage and compute systems, ideally for large, multi-node computations
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