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Experimental Biologist

DataAnnotation DataAnnotation ContractRemote
Posted Oct 8, 2026 · ✓ Still open — checked 3 hours ago

Quick facts

Type
Contract
Location
Remote
Background
PhD
Platform
DataAnnotation — 112 open jobs
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Free to apply — never pay to get AI training work

Pay: up to $40 – $125+ /hour (depends on task difficulty and specialization)

Location: Remote · Type: Independent contractor · Hours: Flexible hours · Payouts: Weekly

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.

Problems draw on whatever you know best:

  • 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).

Compensation

Up to $40 – $125+/hr depending on task difficulty and specialization. Many contributors add $10k–$100k+ a year; some make it their full-time income.

About DataAnnotation

DataAnnotation is where 100k+ experts train the world’s leading AI models. $150M+ paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.

How it works

Apply, pass the qualification assessment, then pick up paid projects whenever you want and get paid weekly.