Job Description

Hummingbird Bioscience is a data-driven precision biotherapeutics team discovering and developing transformative biologic medicines for hard-to-treat diseases. The Hummingbird Bioscience model combines computational and systems biology, wet lab drug discovery in a multi-disciplinary, collaborative environment spanning initial discovery through clinical development. We harness this integrated approach across target identification and patient selection, enabling our team to increase the efficiency of translating novel scientific insights while reducing the inherent risk in drug discovery and development. At Hummingbird Bioscience, our commitment to rigorous science, teamwork, and intellectual integrity underpins our passion to accelerate the journey of new drugs from concept to clinic.

Our highly experienced teams in the US and Singapore span antibody discovery, pharmacology, production and clinical development. For more information, please visit www.hummingbirdbioscience.com, and follow Hummingbird Bioscience on LinkedIn and Twitter.



ABOUT THE ROLE

We are seeking an AI Engineer Intern to implement and test in-house applications of large language models (LLMs). The successful candidate will have a strong background in front-end development, with prior experience in machine learning.

KEY RESPONSIBILITIES

• Develop user-friendly interfaces for in-house applications of ML and LLM models

• Source and curate datasets for model(s) training and refinement

• Finetune LLMs based on specific desired downstream tasks

• Strong programming skills (Python preferred)

• Prior experience with deep learning libraries (e.g. PyTorch and TensorFlow) and/or LLM libraries such as LangChain

• Knowledge of various deep learning architectures as well as ML model training and fine-tuning strategies

• Familiarity with linux command line interface

• Experience with high-performance computing and knowledge of containerization is preferred

• Working knowledge of Git is ideal

InternSG