AI in Residence at Xaira Therapeutics in South San Francisco, CA

Summary: Xaira Therapeutics is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The AI in Residence role is designed for exceptional researchers and engineers to apply advanced AI to biomedical problems, collaborating closely with teams to design, build, and ship machine learning capabilities that influence therapeutic programs. Responsibilities: - Develop and advance ML models for biological, preclinical, and translational datasets (e.g., multimodal omics, imaging, text, assay data) - Design and implement scalable pipelines for data curation, training, evaluation, and inference integrated into discovery workflows - Own projects end-to-end: problem framing → prototyping → validation → deployment - Evaluate robustness and reliability (generalization, uncertainty, failure modes), plus interpretability where it supports scientific decision-making - Contribute technical leadership by proposing new directions, shaping platform capabilities, and raising engineering/research standards through collaboration - Foundation / representation models over multimodal biological and translational data - Methods for small, biased, noisy datasets; distribution shift; and uncertainty estimation - ML systems for experimental prioritization, assay interpretation, or translational signal discovery - Evaluation frameworks and benchmarks tailored to discovery decision-making - Tooling that makes models usable by scientists (interfaces, automation, monitoring) - You ship one or more models or pipelines that are used in real discovery workflows - Your work improves decision quality (e.g., better prioritization, faster iteration, clearer uncertainty) - You raise the bar on evaluation rigor and reproducibility (strong baselines, error analysis, reliable metrics) - You leave behind maintainable systems (tests, documentation, monitoring) that others can build on Required Qualifications: - Recent MS or PhD graduates (or equivalent research experience) in ML/AI, computational biology, biomedical engineering, or related fields - Evidence of research excellence through high-quality publications or artifacts - Demonstrated ability to lead substantial technical work with originality—new modeling ideas, rigorous experiments, or production-grade systems adopted by others - Motivation to translate rigorous research into reliable, deployable AI systems that support therapeutic discovery Preferred Qualifications: - Top venues (e.g., NeurIPS, ICML, ICLR, CVPR, ACL; Nature Methods, Cell Systems) are a plus - Strong preprints, open-source contributions, or shipped systems with demonstrated impact are equally compelling Required Skills: Machine Learning, Data Curation, Biological Data Analysis Important Skills: Systems Thinking Nice-to-Have Skills: Collaborative Execution, Research Judgment Benefits: Dedicated technical mentor, plus structured feedback from senior AI, engineering, and scientific leadership, We value scientific contribution and may support publications and conference presentations when appropriate.