AI Trainer - Life Sciences

About the role

Join a pioneering effort in AI training with a fully remote, 12-week engagement specializing in life sciences research and discovery. We're looking for highly skilled scientists, bioinformaticians, and experimental biologists to evaluate and enhance AI-generated responses, develop challenging reasoning problems, and author rigorous scientific content - all crucial to training next-generation AI systems used in drug discovery and bioinformatics. This role offers a unique chance to contribute directly to cutting-edge AI applications, working independently in a flexible schedule while leveraging your deep scientific expertise.

Responsibilities

• Evaluate and enhance AI-generated responses in life sciences
• Develop challenging reasoning problems for AI training
• Author rigorous scientific content
• Analyze complex biological data
• Design and troubleshoot experiments (experimental biology track)
• Apply computational approaches to reinforce AI capabilities in real-world scientific contexts

Qualifications

This position requires a solid background in your scientific discipline, with 3+ years of hands-on industry or academic experience in discovery environments such as pharma, biotech, or research institutes. The ideal candidate is detail-oriented, possesses strong written communication, and has familiarity with AI tools, especially large language models, to better judge and improve AI responses.

Education Requirements

• Must hold a Master's, PhD, or be a PhD candidate in biology or related fields such as molecular biology, genetics, immunology, neuroscience, biochemistry, bioinformatics, or computational biology
• Degree must be completed in the U.S., Canada, Europe, or the UK (Australia & New Zealand possible)
• Must pass a 3-4 hour paid skills assessment ($240) to qualify for the project
• Fluency in English is essential
• Prior experience working with large language models or in drug discovery can be a significant advantage but is not mandatory

Drug Discovery Track

3+ years of hands-on experience in a discovery or preclinical setting (pharma, biotech, or an academic drug discovery unit)

• Direct experience in at least one of: medicinal chemistry and SAR / lead optimization; computational chemistry or CADD; assay development and screening; DMPK, PK/PD, or ADME; preclinical safety and toxicology; translational and biomarker science; protein or antibody engineering; cell and gene therapy; CMC, formulation, or analytical development
• Strong familiarity with drug discovery workflows, including those involved in how a program moves from target identification and validation, through hit finding and hit-to-lead, into lead optimization and candidate selection, and on into IND-enabling studies
• Nice to have: Experience across more than one modality (small molecule, biologics, cell or gene therapy) or more than one therapeutic area

Computational Biology / Bioinformatics Track

3+ years of hands-on experience analyzing real biological data (industry, an academic lab, or a research institute). Note: Time in an academic lab or research institute must be after undergraduate education.

• Writes, debugs, and can explain their own analysis code in Python and/or R (strong proficiency preferred in both, but at least one)
• Direct experience in at least one of: genomics and variant interpretation; bulk or single-cell transcriptomics; proteomics, metabolomics, or multi-omics integration; population and statistical genetics; machine learning applied to biology; clinical genomics; metagenomics or phylogenetics
• Has independently owned a multi-step analysis end to end (from raw or messy data, through cleaning and processing, to a final interpretation) rather than picking up a clean dataset mid-pipeline
• Familiarity with reproducible research practices (notebooks, scripts, version control, workflow tools)
• Can judge whether a result is real, and say what it means (normalization choices, batch effects and confounding, multiple-testing correction, power, and interpreting results biologically)

Experimental Biology Track

3+ years of experience designing (and running) experiments at a pharma or biotech lab, academic research lab, or CRO

• 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
• Has designed and troubleshot experiments, not only executed established SOPs; can explain what the controls are for and diagnose why a run failed
• Generates and QCs primary data; can look at raw instrument output and judge whether a run is usable before anyone makes a figure from it

Schedule

• 12-week engagement
• Candidates committed to 30-40 hours weekly will be considered
• Fully remote, with a preference for those based in the US; UK and Canada candidates are also eligible, pending confirmation