Life Sciences Ai Trainer

Life Sciences AI Trainer Overview

• As a Life Sciences AI Trainer, contribute to advancing frontier AI models in biological data analysis.
• Engage in fully remote, flexible, project-based AI training work with substantial autonomy.
• Design and evaluate computational biology tasks to improve AI capabilities in life sciences.
• Collaborate with experts to refine AI model outputs and ensure alignment with professional standards.
• Work with realistic biological files, including experimental data, protocols, and analysis reports.
• Contribute to a mission-driven initiative aimed at enabling human-aligned AI development.
• Benefit from flexible scheduling and access to advanced AI tools provided by the client.
• Participate in a structured, self-directed environment emphasizing clear written reasoning and technical depth.

Life Sciences AI Trainer Key Responsibilities & Duties

• Design realistic computational biology tasks based on professional workflows and scenarios.
• Evaluate AI model outputs against professional standards and document results comprehensively.
• Develop detailed grading rubrics specifying correct analysis requirements and reasoning.
• Identify and flag failures in AI outputs with evidence and detailed explanations.
• Contribute expertise across genomics, transcriptomics, proteomics, and machine learning applications.
• Collaborate with other experts to refine tasks and improve AI training methodologies.
• Ensure reproducible research practices using scripts, notebooks, and version control tools.
• Participate in feedback and revision processes to enhance task quality and effectiveness.

Life Sciences AI Trainer Job Requirements

• Bachelor’s degree or higher in Biology, Bioinformatics, or a related field.
• Minimum of 2 years of hands-on experience analyzing biological data in industry or academia.
• Proficiency in Python and/or R for analysis coding and debugging.
• Expertise in genomics, transcriptomics, proteomics, or machine learning applied to biology.
• Strong written communication skills to articulate complex scientific reasoning.
• Comfort with ambiguity and ability to quickly orient in new datasets and workflows.
• Familiarity with AI tools like ChatGPT and Claude for life sciences applications.
• Availability for at least 10 hours per week with flexible scheduling options.