Experimental Biologist

Overview
We’re looking for experienced bench scientists to help train AI models. You’ll design realistic experimental-biology tasks from your own practice, run them through frontier AI systems, and grade what comes back against the standard you’d hold a colleague to.
The models can already talk fluently about biology. What they can’t yet do reliably is the real work: call a plate QC go/no-go, gate a flow panel, check a cloning strategy, or read a Western blot from the raw images. Your bench judgment becomes the benchmark those models are measured against.
What you’ll actually do

• Design realistic experimental tasks from your own workflows: the scenario, the prompt, and the supporting files an agent would need (plate maps and reader output, gel and blot images, flow summaries, protocols, QC records).

• Run tasks through frontier AI agents and grade the deliverable they produce (a QC summary, experimental plan, or troubleshooting memo) against a professional standard.

• Write clear grading rubrics that specify what a correct deliverable must contain (the right controls, the right wells excluded, the right diagnosis of a failed run), and explain why a response passes or fails.

- Flag concrete failures with evidence: controls ignored, edge effects and outliers missed, wrong normalization, plausible-sounding troubleshooting the raw data contradict, or fabricated values.

• Flag concrete failures with evidence: controls ignored, edge effects and outliers missed, wrong normalization, plausible-sounding troubleshooting the raw data contradict, or fabricated values.

• Molecular and cell biology: cloning, cell culture, and cell-based assays.

• Protein biochemistry: purification, characterization, and assay development.

• Immunology and flow cytometry: panel design and gating.

• Imaging and histology, microbiology and virology.

- In vivo and preclinical work, plus lab operations and analytical sciences.
Roles this fits
Common backgrounds: Research Scientist, Molecular / Cell Biologist, Postdoctoral Fellow.
What we look for

• 3+ years designing and running experiments in a pharma, biotech, or academic research lab (counted after undergraduate study).

• Depth in at least one of: molecular biology and cloning; cell culture and cell-based assays; protein biochemistry; immunology and flow cytometry; imaging and histology; microbiology or virology; in vivo and preclinical work.

• A hands-on practitioner who designs and troubleshoots experiments, not only executes SOPs: you can explain what each control is for and diagnose why a run failed.

• You generate and QC primary data, and can judge from raw instrument output whether a run is usable.

• Master’s or PhD (or current PhD candidate) in biology or a related field, completed in the U.S., Canada, Europe, or the UK.

• Clear written English, comfort with ambiguity, and familiarity with AI/LLM tools like Claude or ChatGPT.

- Based in the United States, Canada, or the UK (Ireland and Australia may also be accepted).
How it works
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Work & get paid

Compensation
Up to $125+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income.
About DataAnnotation
DataAnnotation is where 1M+ experts train the world’s leading AI models. Hundreds of millions paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.
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