Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider of choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.
By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.
Our global workforce includes over 5,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel, and Germany. We’re poised for a period of explosive growth over the next few years.
About the Role:
At Innodata, we’re working with the world’s largest technology companies on the next generation of generative AI and large language models (LLMs). We’re looking for smart, savvy, and curious subject matter experts.
We are seeking a Medical Writer Subject Matter Expert with exceptional writing and analytical skills to join our AI/ML data team. In this role, you will help train advanced Large Language Models (LLMs) by producing, curating, and reviewing high-quality medical and scientific content. Your expertise will directly shape the way AI systems understand, explain, and communicate clinical and biomedical information.
Key Responsibilities:
Create high-quality, accurate, and medically sound content, including:
* Clinical and scientific explanations of medical topics
* Research summaries, clinical abstracts, and literature reviews
* Patient education materials
* Medical problem sets, case studies, and evidence-based Q&A
* Regulatory, pharmacological, or public health-focused content (as applicable)
Collaborate with AI researchers and engineers to:
* Review and refine medical-related model outputs
* Identify and address conceptual gaps in LLM training data
* Build diverse datasets across medical and healthcare domains (e.g., anatomy, pathology, pharmacology, public health, epidemiology, evidence-based medicine)
* Provide feedback to improve LLM performance in reasoning, comprehension, and communication of healthcare content
Eligibility Criteria:
* Master’s degree or PhD in Medicine, Biomedical Sciences, Pharmacy, Public Health, or a related healthcare/clinical discipline
* (Exceptional candidates with professional degrees such as MD, DO, PharmD, MPH, or equivalent clinical experience will be considered)
* Strong background in medical/scientific writing, with the ability to communicate complex topics clearly and accurately
* Experience with literature review, evidence synthesis, or regulatory writing is a plus
* Familiarity with scientific publishing standards, citation practices, and biomedical databases (e.g., PubMed, Cochrane)
Additional Requirement:
As part of the project, you are required to complete the English language assessment.
This assessment is mandatory and non-billable.