About the role
About Turing
Turing is one of the world’s leading AGI infrastructure companies, working with frontier AI labs to accelerate model development through high-quality training data, evaluations, and engineering talent.
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
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 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.
Required Skills:
- Minimum 2+ years of overall experience
- Strong experience with at least one of the following languages: Python
- 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: Minimum 40 hours per week with overlap of 4 hours with PST.
- Employment type : Contractor assignment (no medical/paid leave)
- Duration of contract : 2-3 weeks; [expected start date is next week]
- Payment: $20 per approved task
- Location : India, Pakistan, Nigeria, Egypt, Ghana, Bangladesh, Turkey, Mexico
Evaluation Process (approximately 75 mins) :
- Assessment based review