Life Sciences Research (Molecular, Micro, Bioinfo) - AI Trainer

Life Sciences Research (Molecular, Micro, Bioinfo) - AI Trainer

Job Summary:

Join our customer's team as a Life Sciences Research (Molecular, Micro, Bioinfo) - AI Trainer, where your expertise in molecular biology, microbiology, genetics, or bioinformatics will help shape the next generation of artificial intelligence for science. This is a unique opportunity to bridge hands-on scientific research with cutting-edge AI, working remotely in a flexible, collaborative, and innovative environment.

Key Responsibilities:

1. Review and critically evaluate AI-generated content relating to biology, molecular techniques, microbiology, genetics, and bioinformatics.
2. Create and curate high-quality datasets, experiment summaries, scientific prompts, and simulated research scenarios for AI training.
3. Identify inaccuracies, gaps, or missing context in scientific explanations and recommend precise corrections.
4. Collaborate with cross-functional research and AI quality teams to enhance scientific guidelines and best practices.
5. Maintain rigorous standards for accuracy, reproducibility, and ethical alignment in all scientific content.
6. Support the continuous improvement of AI systems by providing expert feedback and insights from a life sciences perspective.
7. Communicate clearly and effectively with both technical and non-technical stakeholders, emphasizing both written and verbal skills.

Required Skills and Qualifications:

1. Bachelor’s, Master’s, or PhD in a life sciences discipline (e.g., Molecular Biology, Microbiology, Bioinformatics, Genetics, Biochemistry, Cell Biology, Biotechnology).
2. Demonstrated experience in laboratory research or computational biology.
3. Strong data analysis and scientific interpretation skills.
4. Exceptional scientific writing and verbal communication abilities, with a keen attention to detail.
5. Proven ability to design experiments and critically assess experimental outcomes.
6. Deep understanding of scientific rigor, reproducibility, and ethical practices in research.

Preferred Qualifications:

1. Experience with next-generation sequencing, omics workflows, or bioinformatics toolkits.
2. Prior involvement in AI, data annotation, or training machine learning models for life science applications.
3. Familiarity with multi-disciplinary research environments and cross-functional teamwork.