This role is for one of our clients Compensation: $70 - $105 per hour Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're looking for Molecular Biology subject-matter experts (SMEs) who have designed DNA and RNA sequences themselves, including primers, pla
About the role
This role is for one of our clients
Compensation: $70 - $105 per hour
Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're looking for Molecular Biology subject-matter experts (SMEs) who have designed DNA and RNA sequences themselves, including primers, plasmids, guide RNAs, mRNA constructs and repair templates, and who can bring that depth to the quality of our AI training data.
Requirements
Key Responsibilities
Work with research and engineering teams to find where a model's molecular biology reasoning breaks down, and help close those gaps.
Design hard, domain-relevant tasks and write the accurate, well documented solutions that become ground truth. That spans primers for PCR, qPCR and cloning, plasmids and expression vectors, gRNA and sgRNA for CRISPR editing, mRNA and RNA constructs, and HDR or repair templates.
Review molecular biology tasks and model outputs against expert-quality solutions, and give clear written feedback on correctness, rigor and biological reasoning.
Write the guidelines and rubrics used to judge sequence design quality, covering guide and target selection, homology arm length, primer melting temperature and specificity, codon optimization, and regulatory elements.
Work alongside other subject matter experts so the training data stays consistent and accurate.
Core Qualifications
An advanced degree, PhD strongly preferred, in molecular biology, genetics, biochemistry, synthetic biology, bioengineering or a related life science field.
Hands-on experience designing nucleic acid constructs before the experiment runs, across several of primers, plasmids and vectors, gRNA and sgRNA, mRNA, and HDR or repair templates, together with the cloning strategy behind them (Gibson, Golden Gate, Gateway, restriction) and codon optimization. …
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