Research Software Engineer

Role Overview

Key Responsibilities

• Design, build, test, & maintain C-Star software components alongside a multidisciplinary, scientifically-oriented team.
• Quickly generate working software prototypes to address emerging needs and user feedback.
• Independently execute on 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.
• Contribute to an organizational culture of cooperation, learning, and adaptation to a changing world.

Minimum Qualifications

• Bachelor’s, Master’s, Doctorate degree, or equivalent work experience in a technical field (e.g., oceanography, atmospheric science, physical science, applied mathematics, computer science).
• Understanding of computationally-heavy scientific modeling workflows, their challenges, and typical user needs. Ocean modeling experience is preferred, but similar earth system modeling experience will also be considered.
• 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 with AI-assisted coding tools is strongly preferred, but we will consider candidates with a strong interest in AI-assisted development and a demonstrated ability to learn and apply new technologies quickly.
• Experience working in small, interdisciplinary, fast-moving teams with shared projects and tasks; demonstrated ability to focus on objectives, iterate towards solutions, and adapt to changing requirements.
• Strong written and oral communication skills, including the ability to translate scientific requirements into software specifications and convey technical results to non-specialist audiences.

Preferred Qualifications

• Experience working with multi-dimensional scientific datasets in Python (e.g., netcdf/zarr formats and Pangeo libraries, particularly Xarray, Numpy, Scipy, and Dask).
• Experience with HPC/supercomputer environments (SLURM, MPI, distributed file systems).
• Expertise in TB/PB-scale data engineering.
• Knowledge of workflow management tools (DAGs, state machines, tracking databases).
• Experience building software intended for reproducibility of results (data versioning, schema versioning, logging, audit trails).
• Experience or interest in natural language interfaces for complex scientific problems (e.g. building AI primitives and skills for running ocean models or interrogating results).
• Familiarity with FORTRAN.
• Experience with GPU-accelerated computation (e.g., CUDA, CuPy, JAX, PyTorch) and running or optimizing numerical/modeling codes on GPUs.

• Junior: $100,000 - $125,000
• Mid-Level: $125,000 - $150,000
• Senior: $150,000 - $175,000