Biology Scientific Coding Evaluator

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. It connects contributors with opportunities to teach and evaluate AI, build credible profiles, and grow experience in a fast-moving technical field.

For this role, OpenTrain AI is hiring a biology-focused scientific coding evaluator for a remote freelance engagement. Creating an OpenTrain account is free, and candidates can apply in minutes.

About AI Training and Scientific Evaluation

AI training is the human side of building artificial intelligence. Specialists create examples, evaluate model outputs, and define what high-quality answers look like so advanced systems become more capable and reliable.

In this role, your scientific judgment will help test whether AI models can solve meaningful biology and scientific computing problems. Your work will contribute to benchmarks that measure model performance on executable research tasks.

The Role

OpenTrain is recruiting a Biology Scientific Coding Evaluator to help build a benchmark for scientific computing. You will create original, executable research problems that test frontier AI models, drawing on expertise in ecology, biochemistry, and genetics.

This is a remote freelance engagement lasting six weeks. The role requires at least 20 hours per week, with a listed default commitment of 40 hours per week, and pays $70 per hour.

• Engagement type: Remote freelance contractor
• Duration: Six weeks
• Time commitment: At least 20 hours per week, with a listed default of 40 hours per week
• Pay: $70 per hour
• Working language: English
• Location: Worldwide

What You’ll Do

You will transform scientific source material and research concepts into clear, executable coding tasks. You will also establish defensible grading standards and test tasks against frontier models to ensure they remain genuinely challenging.

Your work may draw from published papers, Kaggle datasets, open-source repositories, or scenarios you design yourself. You will use software development workflows and automated validation tools to run and assess the resulting code.

• Source suitable material from published papers, Kaggle datasets, and open-source repositories
• Design original scientific computing scenarios when appropriate
• Write clear prompts for executable research tasks
• Define grading criteria for correct answers
• Calibrate tasks against frontier AI models
• Use Git or GitHub pull requests to manage work
• Run automated quality checks and validate code in Docker-based environments
• Evaluate whether model-generated answers are scientifically and technically correct

Required Qualifications

You should bring PhD-level expertise in biology, biological sciences, biochemistry, genetics, ecology, or a closely related discipline. Demonstrated depth in at least two of ecology, biochemistry, and genetics is required.

You must also be able to translate research concepts into executable problems and defensible grading criteria, while applying strong scientific judgment to model-generated answers.

• PhD in biology, biological sciences, biochemistry, genetics, ecology, or a closely related field
• Depth in at least two relevant subdomains, including ecology, biochemistry, or genetics
• Working proficiency in Python, R, or another relevant scientific programming language
• Practical experience with Git or GitHub and pull-request workflows
• Comfort working with Docker and automated code quality checks
• Ability to formulate original, executable scientific computing problems
• Ability to define defensible grading criteria
• Strong scientific judgment and attention to detail

Helpful Background

Experience publishing in peer-reviewed scientific venues or working in scientific software development and research engineering will be valuable in this role.

• Peer-reviewed scientific publications
• Scientific software development experience
• Research engineering experience

Why Work in AI Training

AI training and data-labeling work is a rapidly growing part of the technology industry. Contributors with specialized knowledge help shape how state-of-the-art models reason, generate answers, and perform technical work.

Remote projects can provide flexible ways to apply advanced expertise alongside other commitments. This opportunity lets you use your biology and scientific programming background on challenging problems at the intersection of research and AI.

How to Apply

Apply through OpenTrain to be considered for this remote, six-week Biology Scientific Coding Evaluator engagement. Highlight your biology specialization, relevant subdomains, scientific programming experience, and work with Git, GitHub, Docker, or research software.

• Create or update your free OpenTrain profile
• Show your relevant biology, biochemistry, genetics, or ecology expertise
• Include scientific programming and software workflow experience
• Apply in minutes through OpenTrain