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 on the P&L.
About the Role We are seeking Life Sciences Subject Matter Experts to develop advanced scientific reasoning tasks for LifeSciBench. Unlike coding-focused benchmarks, this role emphasizes deep biological knowledge, scientific interpretation, and rigorous reasoning. You will create challenging questions based on realistic scientific scenarios, experimental results, biological data, figures, literature-style evidence, and research problems. This is a non-code benchmark: tasks are not executed, and no programming is required. Who this is for. Life scientists who want to author rigorous scientific-reasoning problems with objectively defensible answers — no coding involved. If your strength is interpreting experiments, spotting ambiguity, and constructing questions that reward synthesis over recall, this is the fit.
Who this isn't for. If you want to build tasks where agents write and execute code, see GeneBench Pro (genomics), Agentic Life Sciences (broad life-sciences workflows), or Terminal Bench Science (cross-STEM terminal tasks).
Responsibilities
- Design novel, graduate-level life sciences problems grounded in realistic research contexts.
- Develop clear questions and rigorous reference answers with defensible scientific reasoning.
- Interpret experiments, datasets, figures, sequences, structures, and other biological evidence.
- Validate biological claims, calculations, assumptions, and conclusions.
- Identify ambiguity, alternative interpretations, and insufficiently constrained questions.