Biological / Chemistry Subject Matter Exper

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.
Key Responsibilities:
Content Creation & Knowledge Engineering:
Develop
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
Produce high-quality scientific content, including:
Research abstracts and technical white papers
Experimental design summaries
Standard operating procedures (SOPs)
Analytical chemistry workflows and chemical reaction mechanisms
Biomedical case studies, drug development datasets, and molecular pathway analyses
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.
Eligibility Criteria:
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.
Additional Information:
Selected candidates must complete an
English Language Assessment.
Mandatory and non-billable step.