AI Training Specialist – Biology at Turing

AI Training Specialist – Biology | Contractor | Fully Remote | 20–40 hrs/week

Turing is seeking a highly analytical, computationally proficient researcher with a strong background in Biology to help shape the next generation of AI systems. In this role, you will design graduate- and research-level computational biology challenges and implement rigorous Python-based reference solutions that evaluate and enhance the reasoning capabilities of advanced AI models.

About Turing

Based in San Francisco, Turing is the world's leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI. Turing accelerates frontier research through high-quality data, advanced training pipelines, and top-tier AI researchers specializing in coding, reasoning, STEM, and more.

Key Responsibilities

• Design original, graduate- or research-level computational biology problems grounded in real-world biological systems.
• Translate complex biological phenomena into clear, structured computational tasks using Python.
• Develop complete, validated reference solutions with reproducible, well-documented code.
• Create robust test cases and validation pipelines to assess correctness, edge cases, and computational performance.
• Categorize problems by biological domain (e.g., genomics, systems biology, ecology, neuroscience, biophysics) and assign appropriate difficulty levels.
• Evaluate outputs from multiple AI models using structured validation criteria, identifying reasoning gaps, biological inaccuracies, and computational weaknesses.
• Collaborate with reviewers and team members to refine problem quality, clarity, and scientific rigor.
• Structure all tasks for execution and validation in Google Colab, including clear problem statements, defined inputs/outputs, assumptions, constraints, and complete Python reference solutions with validation tests.

Task Design Standards

• Problems must be based on realistic biological scenarios from high-quality scientific literature — not textbook-style exercises.
• Written in clear, concise language with minimal unnecessary jargon.
• Require multi-step reasoning, quantitative analysis, or algorithmic design.
• Encourage models to infer the correct biological and computational approach rather than rely on keyword matching.
• Include realistic constraints, boundary conditions, and potential corner cases.

Required Qualifications

• Preferred: PhD or PhD Candidate in Computational Biology, Bioinformatics, Systems Biology, Biophysics, Molecular Biology, Ecology, Evolutionary Biology, Neuroscience, or a closely related quantitative biological field.
• Also considered: Master's Degree in a related field with a minimum of 2 years of research or industry experience in computational/scientific work.
• At least one peer-reviewed scientific publication.
• Strong proficiency in Python for scientific computing.
• Experience with numerical modeling, statistical analysis, or simulation of biological systems.
• Familiarity with libraries such as NumPy, SciPy, pandas, matplotlib, or relevant bioinformatics tools.
• Ability to design clean, reproducible, and well-documented scientific code.
• Experience with Google Colab or similar notebook environments.
• Strong analytical reasoning and ability to translate biological questions into computational frameworks.

Engagement Details

• Commitment: Minimum 20 hrs/week (options: 20, 30, or 40 hrs/week); at least 4 hrs/day with 4-hour overlap with PST.
• Type: Contractor/Freelancer (no medical or paid leave benefits).
• Duration: 2-month contract with potential for extension based on performance.
• Start Date: Expected next week.

Perks

• Fully remote work environment.
• Opportunity to contribute to cutting-edge AI research with leading LLM companies.
• Potential for contract extension based on performance and project needs.