Senior C# Engineer — Open-Source Vet & Docker/LLM Testing

Turing Global India; United States; Remote; USD 14.000 - 27.000; Vollzeit

Benefits dieser Stelle

Fully remote

Cutting-edge AI projects

Zusammenfassung

Turing Global India is seeking experienced software engineers at the tech-lead level to contribute to high-quality public GitHub repositories. This hands-on role includes development environment automation, issue triaging, and evaluating test coverage and quality.

You will analyze and triage GitHub issues, Dockerize and configure repositories, assess unit test coverage, and run code locally to evaluate LLM performance in bug-fixing scenarios while collaborating with researchers on challenging

Qualifikationen

• Minimum 3+ years of overall experience.
• Strong experience with at least one language: C#.
• Proficiency with Git, Docker, and basic software pipeline setup.
• Ability to understand and navigate complex codebases.
• Comfortable running, modifying, and testing real-world projects locally.
• Experience contributing to or evaluating open-source projects is a plus.

Aufgaben

• Analyze and triage GitHub issues across trending open-source libraries.
• Set up and configure code repositories, including Dockerization and environment setup.
• Evaluating unit test coverage and quality.
• Modify and run codebases locally to assess LLM performance in bug-fixing scenarios.
• Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs.

Kenntnisse

3+ years overall experience

C# experience

Git proficiency

Docker proficiency

Codebase navigation

Testing and QA

Open-source contribution

Tools

Git

Docker

CI/CD

Jobbeschreibung

Turing Global India is seeking experienced software engineers at the tech-lead level to contribute to high-quality public GitHub repositories. This hands-on role includes development environment automation, issue triaging, and evaluating test coverage and quality.

You will analyze and triage GitHub issues, Dockerize and configure repositories, assess unit test coverage, and run code locally to evaluate LLM performance in bug-fixing scenarios while collaborating with researchers on challenging