Role Overview
Turing invites Legal Experts to join projects that fine-tune AI models like ChatGPT. If you enjoy applying legal reasoning, analyzing complex cases, and providing clear, structured feedback, this is your chance to put your expertise to work in a new way. No prior AI experience is required — your background in U.S. law is exactly what’s needed to shape how the next generation of AI understands and reasons about legal systems.
What Does Day-to-Day Look Like
Review and evaluate AI-generated responses to U.S. legal hypotheticals across multiple areas of law.
Apply a structured legal rubric to assess issue spotting, accuracy, reasoning, and application of law.
Identify gaps, edge cases, and blind spots in legal reasoning, helping define benchmarks for legal AI performance.
Provide detailed, high-quality annotations and written feedback to refine AI models.
Collaborate with researchers and project managers to align evaluation standards and project goals.
Requirements
Juris Doctor (J.D.) from an accredited U.S. law school; Bar admission (active/inactive).
3+ years of U.S. legal practice or teaching experience.
Strong reasoning skills across core areas of U.S. law.
Excellent written communication and attention to detail.
High ethical standards; interest in AI is a plus.
Perks of Freelancing with Turing
Opportunity to work on cutting-edge AI projects with leading LLM companies.
Competitive compensation
Flexible, fully remote work arrangement.
Learn how to use AI to advance the legal field.
Offer Details
Commitment: Flexible, 10–30 hrs/week
Duration: ~1 month, with the possibility of extension based on performance and project needs.
About Turing
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results
