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Open nowPosted 27 hours ago

Research Software Engineer

Convergent Research26 open roles

Pay
$100,000 – $175,000 a year
Where
Boulder, CO
Work mode
On site
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Your applicationOpen nowResearch Software EngineerConvergent Research · Boulder, CO

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The clock on this job

Early applications get read.

13.6% of postings close within 7 days. Measured by our own scanner across the market. Convergent Research postings stay open a median of 51 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.7%3 days
  3. 13.6%7 days
  4. 21.9%14 days
  5. 36.9%30 days
  6. 59.0%60 days
This job: posted 27 hours ago

Convergent Research median: 51 days open

The posting

About [C]Worthy

[C]Worthy is a tightly coordinated team of scientists, developers, and leaders moving quickly to accelerate and de-risk ocean-based climate solutions. We are building C-Star, an open-source modeling platform that systematizes ocean modeling through automated, reproducible workflows, enabling reliable, high-fidelity simulations of ocean circulation and biogeochemistry. We use this software to support a range of applications, including ocean-based carbon dioxide removal (CDR), an emerging technology with the potential to make significant contributions to stabilizing the climate system. We are working with external partners to establish a broad user-base within academia, industry, and the larger ecosystem of climate-solutions actors.

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.
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