Hummingbird Bioscience – AI Model Development and Engineering

ABOUT HUMMINGBIRD BIOSCIENCE

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 Research Software Engineer to design, implement and test new neural network model architectures to explore improvements to transformer-based models such as BERT and GPT which can improve reasoning.

KEY RESPONSIBILITIES

• Develop, implement and evaluate model architectures, algorithms, and training strategies 
• Explore and compare model performance to existing models
• Write and/or refactor code to automate pipelines
• Curate suitable training datasets 

ESSENTIAL QUALIFICATIONS & EXPERIENCE

• Strong expertise in deep learning and neural network architectures 
• Demonstrated programming skills in Python and experience with deep learning frameworks such as PyTorch and Tensorflow 
• Familiarity with fine-tuning of pre-existing models 
• A strong background in computer science and/or mathematics would be an advantage