Biology Benchmark Researcher (AI Data Trainer)

In this role, you will collaborate on AI-focused projects involving reasoning, problem-solving, data interpretation, and scientific explanation development. You will also contribute to building evaluation benchmarks for advanced Biology topics ranging from undergraduate to PhD-level concepts.

Responsibilities

• Design and solve challenging Biology problems for AI model evaluation

• Create clear, step-by-step solutions with strong scientific reasoning

• Collaborate with researchers to improve AI model performance

• Contribute to benchmark creation for Biology curricula

• Analyze areas where language models struggle, including abstraction and multi-step reasoning

• Provide detailed annotations and constructive feedback

Required Qualifications

• Master’s degree, Ph.D., Postdoctoral degree, or currently pursuing advanced studies in:

  • Biology

  • Biotechnology

  • Biochemistry

  • Related fields

• Strong research and analytical skills

• Excellent English comprehension and communication skills

• Ability to work independently in a remote environment

• Reliable desktop/laptop and internet connection

• Availability for 40 hours/week with at least 4 hours PST overlap

Technical Requirements

Candidates should be proficient in at least three of the following tools:

BWA, Bowtie2, GATK, HMMER, HHsuite, STAR, SPAdes, IQ-TREE, OpenMM, AlphaFold2, PyOpenMS, RELION, PhysiCell, COPASI, Comet, COBRApy, Hifiasm, ABySS, DeepVariant, Flye, OR-Tools, Bracken, Kraken2, MEGAHIT, antiSMASH, BEAST2, FastTree, DIA-NN, Percolator, AutoDock Vina, CP2K, Salmon, MethylDackel, Canu, and GROMACS.

Additional Notes

• LinkedIn profile must be included in the resume

• Candidates will undergo a background verification after onboarding

• Work allocation begins only after successful verification

• This is a freelance/contractor engagement with no medical or paid leave benefits

Perks

• Fully remote work setup

• Opportunity to work on cutting-edge AI projects

• Collaborate with leading LLM research teams

• Potential contract extension based on performance