About the role
About Xaira Therapeutics Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London.
About
the Role Xaira is seeking a highly motivated and experienced Principal Scientist to join our Functional Genomics team with a focus on high-throughput perturbation platforms and single-cell genomics technologies. The ideal candidate will bring deep expertise in CRISPR-based screening approaches, perturb-seq, and large-scale functional genomics workflows, with experience generating high-quality datasets to support both therapeutic discovery and AI/ML modeling initiatives. This position offers the opportunity to contribute to cutting-edge efforts at the intersection of functional genomics, machine learning, and disease biology. You will work closely with AI/ML scientists, computational biologists, automation engineers, and disease biology teams to develop scalable perturbation workflows, implement new technologies, and drive high-quality data generation and experimental innovation across multiple therapeutic areas. Key
Responsibilities Lead high-throughput perturbation and functional genomics efforts supporting therapeutic discovery and AI/ML-driven research initiatives Develop and implement advanced functional genomics technologies, including perturb-seq, CRISPRi/a, and single-cell omics workflows across complex cellular systems such as primary cells, differentiated cell types, and in vivo models Design, optimize, and scale screening workflows to improve throughput, reproducibility, data quality, and experimental robustness Collaborate closely with AI/ML scientists, computational biologists, automation engineers, and disease biology teams to integrate large-scale perturbation datasets into predictive modeling frameworks Contribute to scientific strategy, experimental design, protocol development, and prioritization across multiple programs and platform initiatives Present scientific findings and contribute to publications, patents, and scientific presentations while mentoring and providing scientific guidance to researchers within the organization
