ML Research Intern, BS/MS - 2026
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About this role
About the Team
Join a world-class team at the forefront of AI and biochemistry.
At Genesis Molecular AI, we’re a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases.
We don’t just apply machine learning to biology; we are conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field. You will work side-by-side with top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations.
About the Role
This is an opportunity to operate as a full member of our research team for the duration of your internship. You will be paired with a mentor and get hands-on experience building and testing models at the forefront of generative AI. Your high-impact project will likely involve working with our foundation models and could touch on cutting-edge areas like diffusion models, large language models (LLMs), or reinforcement learning. We’re looking for exceptional students passionate about applying their technical skills to challenging research problems and contributing directly to our mission.
You Will
- Contribute to a high-impact research project by building models, running experiments, and analyzing results for a key scientific challenge in generative AI.
- Turn research ideas into high-quality code, implementing and optimizing multi-modal models and algorithms from the latest literature.
- Design and run experiments at scale to validate promising approaches and hypotheses.
- Present your work and findings to the team, contributing to our collaborative research environment.
You Are
- Currently enrolled in a Bachelor's or Master's program in Computer Science, Machine Learning, or a related technical field.
- A skilled and agile coder with a passion for writing clean, efficient, and reliable code.
- A curious and tenacious problem-solver, excited to tackle complex technical challenges.
- Eager to learn about the intersection of AI and biochemistry and the drug discovery process.