AI Trainer (Life Sciences)

About the Role

We are looking for expert Computational Life Scientists to help refine sophisticated artificial intelligence platforms. This position is tailored for professionals with a strong background in AI model assessment or training within the biomedical or life sciences sectors. You will utilize your technical skills to advance AI performance, ensuring outputs adhere to strict scientific methods. Your focus will be on pinpointing model reasoning failures and creating objective benchmarks for scientific computing. As an independent contractor, you will operate in a flexible setting where your specialized expertise shapes the evolution of future models. You will be tasked with creating intricate assignments that test how well the system processes complex technical or biological information. Through careful performance review, you will help align theoretical AI potential with tangible, reproducible scientific inquiry. This role suits experts who excel in autonomous, project-driven work and are motivated to apply their research experience to the advancement of artificial intelligence.

Requirements

• Documented professional history in evaluating, benchmarking, or training AI systems for technical or scientific applications.
• Extensive knowledge in a life-science discipline, including bioinformatics, computational biology, genomics, biomedical science, or neuroscience.
• Advanced practical Python skills paired with direct experience in reproducible research, simulations, or statistical analysis.
• Submission of verifiable evidence of your proficiency, such as open-source software contributions, research code, peer-reviewed articles, or involvement in biomedical challenges.
• Proficiency with scientific tools such as pandas, SciPy, NumPy, and PyTorch is strongly preferred, along with prior experience in evaluating agentic AI.

Responsibilities

• Design sophisticated computational life-science assignments to stress-test advanced AI models.
• Develop precise task instructions, reproducible setups, and provide reference solutions paired with detailed evaluation metrics.
• Perform critical assessments of code, scientific data, and experiments produced by AI to uncover statistical errors, methodological flaws, false biological premises, or data leakage.
• Set high benchmarks for accurate and dependable results to maintain the quality of training data used for AI systems.

Benefits & Perks

• A flexible work schedule is provided, requiring a minimum of 15 hours per week.
• Compensation is based on performance, with an equivalent rate between $60 and $120 per hour, distributed per approved task.