About this Opportunity:
We are seeking skilled professionals to contribute their expertise in Biological & Biomedical Sciences and Chemistry to a team focused on developing AI/ML models.
This role involves leveraging scientific knowledge to curate, validate, and create domain-specific content that enhances AI reasoning and performance in life sciences and chemical sciences.
The successful candidate will play a key role in training advanced LLMs and scientific AI systems by developing datasets, reviewing model outputs, and ensuring alignment with scientific accuracy, regulatory compliance, and ethical standards.
Key Responsibilities:
* Content Development:
Create scientifically accurate, domain-rich datasets in: Molecular Biology, Biochemistry, and Genetics Pharmacology and Biomedical Engineering Chemistry (Organic, Inorganic, Physical, Analytical, Computational) Cell and Developmental Biology, Immunology, Microbiology Biotechnology, Toxicology, and Chemical Engineering
* Ai Model Evaluation & Data Refinement:
Validate AI-generated outputs for accuracy, reproducibility, and compliance with scientific and safety standards. Identify and correct conceptual errors, dataset biases, or incomplete knowledge representations. Contribute to knowledge graph development and ontology engineering for biological and chemical datasets.
* Cross-Disciplinary Collaboration:
Collaborate with AI engineers, data scientists, and computational chemists to optimize model reasoning. Support the creation of adversarial testing datasets for LLMs in biomedical and chemical domains. Participate in R&D discussions to enhance AI performance in drug discovery, materials science, and biomedical research applications.
Requirements:
Advanced degree required: Master's, PhD, or equivalent in Biology, Biomedical Sciences, Chemistry, Biochemistry, Molecular Biology, Chemical Engineering, or a related field. Strong expertise in laboratory research, computational modeling, bioinformatics, or chemical analysis. Proven experience in scientific writing, peer-reviewed publication, or technical documentation. Familiarity with regulatory frameworks, laboratory safety, and ethical research guidelines. Preferred experience with: Computational chemistry, cheminformatics, or molecular modeling software. Bioinformatics pipelines, omics data analysis, and high-throughput screening methodologies.