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A data engineering and AI technology provider is seeking a Subject Matter Expert in Biological & Biomedical Sciences and Chemistry. This role involves developing datasets for AI training and ensuring scientific accuracy in content creation. Candidates should hold an advanced degree and have strong expertise in laboratory research and scientific writing. The position emphasizes collaboration with AI engineers and data scientists to enhance AI performance, making it pivotal in the fields of life sciences and chemical sciences.
Job Title : Biological & Biomedical Sciences / Chemistry Subject Matter Expert – AI Training & Content Development
About Innodata :
Innodata (NASDAQ : INOD) is a global leader in data engineering and AI-powered technology solutions, trusted by 2,000+ enterprise customers worldwide, including 4 of the top 5 global technology companies. With operations in 13 cities and a workforce of over 5,000 experts across the United States, Canada, the UK, the Philippines, India, Sri Lanka, Israel, and Germany, Innodata is at the forefront of artificial intelligence (AI), natural language processing (NLP), and large language model (LLM) innovation.
We combine cutting-edge ML / AI technologies, deep scientific expertise, and high-security infrastructure to deliver next-generation solutions for industries spanning pharma, life sciences, healthcare, technology, finance, and law.
About the Role :
We are seeking Subject Matter Experts (SMEs) in Biological & Biomedical Sciences and Chemistry to join our AI / ML model training and content development team. In this role, you will leverage your scientific expertise to curate, validate, and create domain-specific content that improves AI reasoning, knowledge representation, and performance in life sciences and chemical sciences.
You will directly contribute to the training of advanced LLMs and scientific AI systems by developing datasets, reviewing model outputs, and ensuring alignment with scientific accuracy, regulatory compliance, and ethical standards.
Responsibilities
Content Creation & Knowledge Engineering :
AI Model Evaluation & Data Refinement :
Cross-Disciplinary Collaboration :
Eligibility Criteria :
Additional Information :