Principal Scientist, Antibody Engineering & Rational Design (South San Francisco)

Who We Are:Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science, and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs. Position Description:We are seeking an innovative Principal Scientist to bridge the gap between traditional antibody discovery and cutting-edge computational design. In this role, you will serve as the primary scientific liaison between wet-lab antibody team and our machine learning engineers, driving the evolution of our Design-Build-Test-Learn cycle.Acting as both a project leader and technical expert, you will translate complex in silico designs into actionable experimental workflows. You will be responsible for ensuring that computational predictions are rigorously validated and that the resulting biological data is structured to retrain and refine our internal models. We are looking for a deep expert in therapeutic antibody development who is eager to move beyond traditional random screening and champion a rational, data-driven approach to biologic drug discovery.Position Requirements:Ph.D. in molecular biology, biochemistry, computational modeling, structural biology, or related discipline8+ years’ post-PhD experience in antibody/protein engineering within the biotech or biopharma industryDemonstrated ability to work intimately with data scientists and ML engineers and able to articulate biological constraints (e.g., immunogenicity, manufacturability) to computational teams and interpret their in silico outputs for experimental validationHands-on proficiency with structural modeling and extensive knowledge in ML protein design toolsExperience designing experiments specifically to generate high-quality training data for ML models (e.g., focused libraries, systematic mutagenesis) is highly desirableExtensive experience in rational design for humanization, affinity/specificity optimization, pH-dependence, and liability removalExperience in engineering multi-specific antibodiesStrong understanding of biophysical characterization to ensure designed molecules are developable therapeuticsExperience technically managing CROs for in vivo and in vitro discovery of antibodies, gene synthesis, protein production, and screening assaysAbility to propose novel scientific approaches and solve complex technical hurdles independentlyMust be willing to work onsite 5 days a weekThe estimated base salary range for this role is $198,000 - $241,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.