AI in Residence

The role

You will develop and advance machine learning models for biological, preclinical and translational data. You will own projects end to end, from problem framing to deployment, working with AI scientists, engineers and drug discovery teams at Xaira Therapeutics.

What you will do

• Develop and advance ML models for biological, preclinical and translational datasets
• Design and implement scalable pipelines for data curation, training, evaluation and inference
• Own projects end to end: problem framing, prototyping, validation and deployment
• Evaluate robustness and reliability, including generalization, uncertainty and failure modes
• Contribute technical leadership by proposing new directions and raising engineering and research standards

Required qualifications

• Recent MS or PhD graduate, or equivalent research experience, in ML/AI, computational biology, biomedical engineering or a related field
• Evidence of research excellence through high-quality publications or artifacts, such as strong preprints, open-source contributions or shipped systems with demonstrated impact
• Demonstrated ability to lead substantial technical work with originality
• Motivation to translate rigorous research into reliable, deployable AI systems for therapeutic discovery
• A brief cover letter describing your interest in the role, why you are excited about this area and what you hope to gain

Nice to have

• Publications at top venues such as NeurIPS, ICML, ICLR, CVPR, ACL, Nature Methods or Cell Systems

Benefits

• Dedicated technical mentor
• Structured feedback from senior AI, engineering and scientific leadership
• Possible support for publications and conference presentations, subject to internal review

Before you apply

• Publication scope and timing are subject to internal review, including IP and confidentiality
• Program is a residency for a small, highly selective cohort

About the company

Xaira is a biotech startup using AI to transform drug discovery and development. It develops generative AI models for protein and antibody therapeutics and foundation models for biology and disease.