Job Description
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:
* At least 3 years of experience at top-tier product or research companies (e.g., Stripe, Datadog, Snowflake, Dropbox, Canva, Shopify, Intuit, PayPal, or research roles at IBM, GE, Honeywell, Schneider, etc.), with a total of 7+ years of overall professional software engineering experience.
* 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)
* Rates: $40–$100/hour, based on experience and skill level.