About Us
Turing is one of the world’s fastest-growing AI companies, pushing the boundaries of AI-assisted software development. Our mission is to empower the next generation of AI systems to reason about and work with real-world software repositories. You’ll be working at the intersection of software engineering, open-source ecosystems, and frontier AI.
Project Overview
We're building high-quality evaluation and training datasets to improve how Large Language Models (LLMs) interact with realistic software engineering tasks. A key focus of this project is curating verifiable software engineering challenges from public GitHub repository histories using a human-in-the-loop process.
Why This Role Is Unique
Collaborate directly with AI researchers shaping the future of AI-powered software development.
Work with high-impact open-source projects and evaluate how LLMs perform on real bugs, issues, and developer tasks.
Influence dataset design that will train and benchmark next-gen LLMs.
What does day-to-day look like:
Review and compare 3–4 model-generated code responses for each task using a structured ranking system.
Evaluate code diffs for correctness, code quality, style, and efficiency.
Provide clear, detailed rationales explaining the reasoning behind each ranking decision.
Maintain high consistency and objectivity across evaluations.
Collaborate with the team to identify edge cases and ambiguities in model behavior.
Required Skills
7+ years of professional software engineering experience, ideally at top-tier product companies (e.g., Stripe, Datadog, Snowflake, Dropbox, Canva, Shopify,Intuit,PayPal, Research at IBM/GE/Honewell/Scheinder etc. ).
Strong fundamentals in software design, coding best practices, and debugging.
Excellent ability to assess code quality, correctness, and maintainability.
Proficient with code review processes and reading diffs in real-world repositories.
Exceptional written communication skills to articulate evaluation rationale clearly.
Prior experience with LLM-generated code or evaluation work is a plus.
Bonus Points
Experience in LLM research, developer agents, or AI evaluation projects.
Background in building or scaling developer tools or automation systems.
Engagement Details
Commitment: ~20 hours/week (partial PST overlap required)
Type: Contractor (no medical/paid leave)
Duration: 1 month (starting next week; potential extensions based on performance and fit)