AI Trainer: Life Sciences:

Brunel•New York, NY

52d•$60 - $125•Remote

About The Position

Brunel is partnering with DataAnnotation to connect experienced Life Sciences professionals with an innovative AI training program. This opportunity brings together deep scientific expertise and artificial intelligence to help evaluate and improve AI-generated content across the Life Sciences. Selected experts will contribute their knowledge to the development of high-quality, scientifically accurate AI systems. This opportunity is designed for scientists and researchers with deep technical expertise across drug discovery, computational biology and bioinformatics, or experimental biology.

Requirements

Master’s or PhD — or a current PhD candidate — in Biology or a directly related field, including molecular or cell biology, genetics, immunology, neuroscience, biochemistry, bioinformatics, or computational biology.
Degree must be completed in the U.S., Canada, Europe, the UK, or Australia.
3+ years of hands-on experience in the relevant subfield.
Full professional/native-level written and spoken English.
Strong written communication skills.
Comfort working independently in a fully remote environment.
Comfort with ambiguity and strong attention to detail.
Ability to orient within a company data package ranging from 100MB to 30GB+ and quickly build an accurate, deep working picture of it, especially when the science sits partly or wholly outside your own specialization.
General familiarity with AI/LLM tools; user-level familiarity is sufficient.

Responsibilities

Evaluate and improve AI-generated content across the Life Sciences.
Contribute scientific knowledge to the development of high-quality, scientifically accurate AI systems.
Interpret feedback, judge its correctness, and apply it independently.
Independently seek answers when encountering difficulties.
Ramp up quickly on unfamiliar work using written materials and instructions, even if incomplete.
Use large language models in life sciences professional work, distinguishing well-reasoned answers from incorrect ones.