Member of Technical Staff, Computational Biology

Member of Technical Staff, Computational Biology LocationSan FranciscoEmployment TypeFull timeLocation TypeOn-siteDepartmentR&DAbout UsRadical Numerics is an AI research lab building general biological intelligence. Our mission is to master the code of life, and our purpose is to reduce human suffering.Our team created Evo, and started the field of generative genomics. Our work was featured on the cover of Science, and presented by our CEO on the main stage of TED2025. Evo was used to create the first AI gene therapy tool CRISPR-Cas9, and the first AI whole genome from scratch. Evo 2, featured in Nature, is the largest fully open source AI project across any domain.Radical Numerics is bringing the rigor of distributed systems, model architecture, and numerics research to the challenges of biology. We’ve redesigned the foundation model training stack to turn the world’s raw scientific data (e.g. biological sequences, experiments, and physical processes), into intelligible, generative models that can expand and accelerate what humanity can understand, design, and cure.The same generative breakthroughs that enable life-saving cures also lowers the barrier to creating engineered threats and AI-generated bioweapons. We believe these forces are inseparable. Radical Numerics was founded to develop both the power to design and the responsibility to defend.About the Role  As a science-focused Member of Technical Staff, you will curate the multimodal biological datasets that power our models, analyze model behavior, and ensure our model outputs meet rigorous scientific standards. You'll co-develop benchmarks, filters, and validation pipelines with engineering peers so biological world models remain trustworthy and actionable.What You'll Do Source, normalize, and steward large-scale genomic, epigenomic, transcriptomic, proteomic, and imaging datasets with rigorous metadata and provenance.  Build evaluation suites and benchmarks that stress-test generative biological models across modalities and tasks.Partner with AI engineers to analyze model outputs, run ablations, and surface insights that guide future architecture and training improvements.  Integrate new datasets and annotations from external collaborators while maintaining compliance, privacy, and ethical standards.  Communicate findings and best practices across Radical Numerics so teams can trust and act on model results.What We're Looking ForPhD in genetics, computational biology, or a related field, OR demonstrated experience in biotech with a strong track record of impact over 3+ years.Proven experience curating, harmonizing, and analyzing large biological datasets (e.g., genomics, single-cell, spatial, or imaging).Fluency with Python, data tooling, and reproducible workflows (git, notebooks, containers).  Ability to interrogate model outputs, debug unexpected behaviors, and translate findings into actionable recommendations.Clear communicator who can bridge scientific context with engineering teams and partner organizations.Curiosity and resilience when tackling open-ended scientific challenges.Nice to Have Familiarity with generative model evaluation, red-teaming, or safety analysis in scientific domains.Experience with statistical validation, quality control, or benchmarking for scientific or ML systems.Experience building benchmarking frameworks or open datasets that became community standards.  Contributions to shared analytics tooling or reproducible research pipelines.Why Radical Numerics Help produce the multimodal biological world models that will power rapid detection, response, and countermeasures across global health.  Collaborative culture that values rigor, creativity, and cross-disciplinary partnership across AI labs, biotechs, hospital systems, and national research institutes.  Competitive compensation, comprehensive benefits, and support for continual learning.Radical Numerics is committed to equal employment opportunity and does not discriminate in any...