Domain Expert – Python at Turing

Aitrainer; San Francisco (CA); Remote; USD 83,000 - 138,000; Part time

Benefits offered by this job

Flexible working hours

Remote collaboration

Competitive compensation

Job summary

Turing is seeking Life Sciences Subject Matter Experts to craft advanced scientific reasoning tasks for LifeSciBench. This non-code benchmark emphasizes deep biology knowledge, experimental 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.

Qualifications

• Ph.D., postdoctoral experience, or equivalent advanced research experience in the life sciences.
• Strong expertise in at least one biological discipline.
• Demonstrated ability to interpret scientific experiments, data, and research findings.
• Strong scientific writing skills and attention to precision.

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.
• Ensure tasks are self-contained, reproducible where applicable, and clearly documented.
• Incorporate reviewer feedback while maintaining quality and throughput.

Skills

Chemistry

Education

Ph.D./Postdoctoral experience

Job description

Create advanced life sciences questions based on real research scenarios.

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.
• Ensure tasks are self-contained, reproducible where applicable, and clearly documented.
• Incorporate reviewer feedback while maintaining quality and throughput.

Required Qualifications

• Ph.D., postdoctoral experience, or equivalent advanced research experience in the life sciences.
• Strong expertise in at least one biological discipline.
• Demonstrated ability to interpret scientific experiments, data, and research findings.
• Strong scientific writing skills and attention to precision.

Relevant backgrounds include molecular biology, genetics and genomics, cell biology, biochemistry, neuroscience, microbiology, immunology, evolutionary biology, ecology, structural biology, biophysics, developmental biology, cancer biology, pharmacology, and related life sciences disciplines.

Preferred Qualifications

• Experience designing graduate-level problems, assessments, or research exercises.
• Experience reviewing scientific manuscripts or research.
• Ability to translate complex scientific concepts into precise, self-contained questions.
• Experience evaluating AI-generated scientific responses or working with AI/ML evaluation datasets.
• Peer-reviewed publications or graduate-level teaching and mentoring experience.

Important Note

This role does not involve programming or executing code. For coding-based or workflow-oriented opportunities, please explore GeneBench Pro, Agentic Life Sciences, or Terminal Bench Science.

Offer Details

• Commitments Required: at least 8 hours per day and minimum 40 hours per week with 4 hours of overlap with PST.
• Engagement type: Contractor assignment/freelancer (no medical/paid leave)
• Duration of contract: 1 month

Benefits

• Opportunity to work on cutting-edge AI projects.
• Competitive compensation.
• Flexible working hours and remote work environment.

Evaluation Process

• Job interest form
• Assessment
• Based on the answers and scores, you will be contacted to discuss the pre-onboarding requirements

Skills

Chemistry