About the projects: We are building LLM evaluation and training datasets to train LLMs to work on realistic software engineering problems. One of our approaches in this project is to build verifiable SWE tasks based on public repository histories using a synthetic approach with a human-in-the-loop, while expanding dataset coverage to include different types of tasks across programming languages, difficulty levels, etc. About the Role:
We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public GitHub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality Why Join Us?
Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research What does day-to-day look like:
Analyze and triage GitHub issues across trending open-source libraries.
Set up and configure code repositories, including Dockerization and setting setup.
Evaluate 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.
Opportunities to lead a team of junior engineers to collaborate on projects.
Required
Skills
Minimum 3+ years of overall experience
Strong experience with at least one of the following languages: Ruby
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. Nice to Have:
Previous participation in LLM research or evaluation projects.
Experience building or testing developer tools or automation agents. Perks of Freelancing With Turing:
Work in a fully remote environment.
Opportunity to work on cutting-edge AI projects with leading LLM companies.
Offer
Details
Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week)
Employment type: Contractor assignment (no medical/paid leave) Evaluation Process (approximately 75 mins) :
Two rounds of interviews (60 min technical + 30 min technical & cultural discussion)