Research Software Engineer

About [C]Worthy
[C]Worthy is a Focused Research Organization operating in partnership with Convergent Research. We develop science-backed tools for Monitoring, Reporting, and Verification (MRV) by adapting advanced oceanographic models to quantify carbon removal and assess ecosystem impacts with scientific credibility. These tools are delivered through our open-source software platform, C-Star, which is designed to ensure ease-of-use, standardization, auditability, and transparency—foundations for building high-integrity CDR markets. We collaborate with early commercial actors in the carbon removal market to support research, provide robust MRV solutions, and shape effective standards. We are also maintaining and building strong connections within the research community to ensure that our tools evolve alongside the best available science and technology.

Position Description
We are seeking an experienced scientific software engineer to contribute to C-Star, our open-source toolkit for high‑fidelity physical–biogeochemical models that are robust, user-friendly, reproducible, and auditable. C-Star encompasses a wide range of scientific and engineering tools that aim to streamline the entire process of running a large ocean model: from initial data gathering and transformations, to distributed, automated model execution, to aggregation and extraction of key results. This provides an opportunity to utilize a broad set of technical skills including workflow management, HPC paradigms (e.g. MPI), complex data transformations (e.g. 3D regridding), scaled data engineering, schema design, cloud/HPC hybrid environments, DevOps, and more. The successful candidate will have a strong foundation in Python software development, with one or more supporting skill sets, and the ability to grow into new technical areas as needed. We are open to considering mid-level to senior candidates based on experience and role fit.

The primary impact of this position is the software that you will help create. While opportunities to author or co-author scientific publications may present themselves, they are not a core focus of this position.

This is a hybrid position with an expectation of three in-office days per week in Boulder, CO.

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