Molecular Biologist

• Job Description
• Molecular Biologist
• Contract
• Remote

Job Summary

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Key Responsibilities

• Lead the design, optimization, and execution of CRISPR-based gene editing experiments.
• Develop and implement cloning strategies to generate novel constructs and cell lines.
• Perform genotyping, PCR-based assays, and sequence analyses to validate genetic modifications.
• Design synthetic DNA/RNA sequences and contribute to screening logic for high-throughput workflows.
• Collaborate with interdisciplinary teams to translate experimental data into structured formats for AI model training.
• Apply molecular biology techniques to study and characterize molecules, organelles, and cellular organization.
• Document experimental procedures and results with exceptional clarity and precision, supporting reproducibility and knowledge transfer.

Required Skills and Qualifications

• Expertise in CRISPR technology and gene editing workflows.
• Extensive hands-on experience with cloning, genotyping, and PCR-based assays.
• Strong background in sequence design and molecular screening strategies.
• Excellent written and verbal communication skills, with keen attention to scientific detail.
• Ability to research and analyze molecular and organelle functions within cells.
• Demonstrated commitment to data accuracy, workflow optimization, and experimental rigor.
• Self-driven and collaborative, with a track record of contributing to high-impact research projects.
• Bachelor’s degree or higher in Molecular Biology, Biology, or a related field.

Preferred Qualifications

• Experience with the development or evaluation of rubrics, especially for AI and data annotation workflows.
• Familiarity with designing datasets or protocols for AI training and human review processes.
• Previous collaboration with interdisciplinary or remote teams on data-driven biology projects.