AI Research Scientist (Intern)
GenMD • United States
Posted: January 26, 2026
Job Description
About Us
GenMD is unlocking healthcare data at scale. Today, roughly 97% of healthcare data goes unused because of patient privacy concerns. We’ve found a way to unlock that data—safely and ethically—for AI labs, pharma companies, and researchers. This isn’t a chatbot, or an AI agent replacing clinicians or automating paperwork. It’s core infrastructure that enables better drugs, faster clinical trials, and more powerful medical research—the kind of foundation that makes real breakthroughs, including curing diseases, possible.
The company was built out of years inside Stanford Medicine, working closely with world-class researchers and clinicians. We have access to tens of millions of patients, longitudinal health records, and clinical notes. GenMD is just coming out of stealth, already revenue-generating, well-funded, and backed by premier investors with years of runway. We’re intentionally small, move fast, and are focused on building something fundamental.
Your Mission
Improve and extend our deep learning and LLM-based models through hands-on research and implementation.
Design, train, fine-tune, and evaluate models with a focus on real-world performance.
Translate research ideas into working code and reproducible experiments.
Collaborate closely with engineers to move models from research to usable systems.
Contribute directly to the technical core of the product.
Requirements
Currently enrolled in an MS/PhD program in Computer Science, AI, Machine Learning, or a closely related field.
Strong foundation in machine learning, deep learning, and NLP, demonstrated through research or projects.
Hands-on experience training and fine-tuning LLMs (modeling, optimization, evaluation).
Strong coding skills in Python and experience with modern ML libraries (e.g., PyTorch, TensorFlow, Hugging Face).
Comfortable working independently in a fast-moving, startup research environment.
Culture
High ownership, high intensity, zero passengers.
We don’t hire for culture fit—we hire people who create culture.
Benefits
Competitive comp + meaningful equity.
Team offsites, conferences, late nights building something real.
Perks evolve with the team—we’re early and intentional.
Additional Content
About Us
GenMD is unlocking healthcare data at scale. Today, roughly 97% of healthcare data goes unused because of patient privacy concerns. We’ve found a way to unlock that data—safely and ethically—for AI labs, pharma companies, and researchers. This isn’t a chatbot, or an AI agent replacing clinicians or automating paperwork. It’s core infrastructure that enables better drugs, faster clinical trials, and more powerful medical research—the kind of foundation that makes real breakthroughs, including curing diseases, possible.
The company was built out of years inside Stanford Medicine, working closely with world-class researchers and clinicians. We have access to tens of millions of patients, longitudinal health records, and clinical notes. GenMD is just coming out of stealth, already revenue-generating, well-funded, and backed by premier investors with years of runway. We’re intentionally small, move fast, and are focused on building something fundamental.
Your Mission
Improve and extend our deep learning and LLM-based models through hands-on research and implementation.
Design, train, fine-tune, and evaluate models with a focus on real-world performance.
Translate research ideas into working code and reproducible experiments.
Collaborate closely with engineers to move models from research to usable systems.
Contribute directly to the technical core of the product.
Requirements
Currently enrolled in an MS/PhD program in Computer Science, AI, Machine Learning, or a closely related field.
Strong foundation in machine learning, deep learning, and NLP, demonstrated through research or projects.
Hands-on experience training and fine-tuning LLMs (modeling, optimization, evaluation).
Strong coding skills in Python and experience with modern ML libraries (e.g., PyTorch, TensorFlow, Hugging Face).
Comfortable working independently in a fast-moving, startup research environment.
Culture
High ownership, high intensity, zero passengers.
We don’t hire for culture fit—we hire people who create culture.
Benefits
Competitive comp + meaningful equity.
Team offsites, conferences, late nights building something real.
Perks evolve with the team—we’re early and intentional.