SWE (Active Open Source Github Contributor)

Auto Import

Mercor is seeking experienced software engineers to support a leading AI lab in advancing research and infrastructure for next-generation machine learning systems. This engagement focuses on diagnosing and solving real issues derived from major open-source repositories through hands-on coding, debugging, and validation. It’s an opportunity to contribute your technical expertise to cutting-edge AI research.

Key Responsibilities

  • Analyze and resolve software issues drawn from large open-source codebases

  • Write, test, and validate code solutions that address specific bugs or system inefficiencies

  • Implement and refine APIs, database structures, and backend components supporting AI workflows

  • Configure local development environments to replicate and investigate complex issues

Ideal Qualifications

  • 3+ years of professional software engineering experience in a fast-paced or technically demanding environment

  • Proven contribution history to one or more of the following open-source repositories is a must. We will be validating this:

    • astropy/astropy

    • django/django

    • matplotlib/matplotlib

    • pytest-dev/pytest

    • scikit-learn/scikit-learn

    • sphinx-doc/sphinx

    • sympy/sympy

  • Advanced proficiency in Python, API development, and structured testing

  • Excellent analytical, written, and communication skills

  • Exceptional attention to detail and persistence in debugging complex systems

  • Residency in one of the following regions: United States, United Kingdom, Canada, Australia, or New Zealand.

More About the Opportunity

  • Expected workload: 20–30 hours per week, with flexibility to scale up to 40 hours

  • Duration: open-ended engagement with potential for long-term collaboration

  • Project start date: mid to late October (applications reviewed on a rolling basis)

Application Process

  • Submit your resume and include links to your GitHub profile and relevant repository contributions

  • Applications reviewed continuously; shortlisted professionals will be contacted for next steps

  • Typical response time: within one week of submission

Back to blog