Engineering Expert

Future projects, not immediate vacancies. Check each network's country and experience requirements. We are seeking Life Sciences Subject Matter Experts to design advanced scientific-reasoning tasks for LifeSciBench. This is a non-coding role focused on biological knowledge, experimental interpretation, data analysis, and rigorous scientific reasoning. Official job description checked 2026-10-24: 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 design advanced scientific-reasoning tasks for LifeSciBench. This is a non-coding role focused on biological knowledge, experimental interpretation, data analysis, and rigorous scientific reasoning. You will create challenging, objectively defensible problems based on realistic research scenarios, experimental results, biological data, figures, sequences, structures, and literature-style evidence. Tasks should test synthesis and interpretation rather than factual recall and help distinguish advanced AI reasoning capabilities. 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. 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. 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 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 Confirm current eligibility, workload and final terms with Turing. Referral rewards are separate from applicant compensation. Compensation context Compensation is not stated in the current feed. Confirm the rate and workload before accepting an assessment or project. Ability to translate complex scientific concepts into precise, self-contained questions. Not the right fit? Compensation is not stated in the current feed. Confirm the rate and workload before accepting an assessment or project. How should I compare the listed pay? Compensation is not stated in the current feed. Confirm the rate and workload before accepting an assessment or project. #J-18808-Ljbffr HumanitApp