Teams at AbSci

Develop and deploy AI and deep learning models for antibody drug design, including test-time compute strategies, multi-objective optimization, target-specific design, and protein structure prediction. Analyze in silico and in vitro validation results, improve design methodologies, publish high-impact research, collaborate across computational and experimental teams, and communicate findings to interdisciplinary audiences.

Develop and deploy deep learning models for AI-guided antibody drug discovery and target identification. Design experiments, build systems biology models, and create in silico and in vitro validation approaches. Collaborate with biological and wet-lab teams, present findings, publish high-impact research, and mentor scientists and engineers.

Own the vision, strategy, roadmaps, and deployment of AI and laboratory products supporting biologics discovery. Lead cross-functional teams of AI/ML researchers, engineers, and life scientists developing platforms for AI-guided target identification and drug design. Gather requirements, prioritize backlogs, define OKRs and KPIs, manage stakeholders, remove execution blockers, conduct user research, and drive product adoption across internal programs and external partnerships.