AI Research Scientist II

Company Overview  We are the only AI-native biotech, pioneering small and large molecule therapeutics discovery by integrating massive multimodal data, frontier AI models, and high-throughput lab automation into an infrastructure for AI-enabled drug discovery.  We hire top 1% talent to join our interdisciplinary team of scientists, engineers, researchers, operators, innovators, drug developers, business professionals, and technologists.   Join us to build the world’s first AI infrastructure for tech-enabled drug discovery and to deliver a pipeline of diverse drug modalities for all major disease areas. As an AI Research Scientist II at 1910 you will be expected to roll up your sleeves as an Individual Contributor (IC) by keeping up with relevant scientific literature, prototyping promising methods, and contributing to our active drug design campaigns by applying 1910’s productionized AI/ML models.    Role Description  Propose and prototype AI and Machine Learning solutions that address use cases in 1910’s design pipeline   Apply productized AI and Machine Learning models to advance 1910’s active drug design campaigns with minimal support from senior members of the AI Research Team  Write and publish peer reviewed scientific articles with minimal support from senior members of the AI Research Team  Periodically presenting recent AI research at internal journal clubs   Work cross-functionally with scientific colleagues, being a subject matter expert in how AI and Machine Learning can be used to answer cheminformatics and bioinformatics questions   Keep up-to-date on cutting-edge research in the AI for drug discovery space     Qualifications  PhD in a relevant discipline (Computer Science, Biology, Chemistry, etc.)  2 years of relevant industry experience (AI, Drug Discovery, etc.)  A strong understanding of statistics and classical machine learning methods (SVM, RF, etc.)   Industry experience training and deploying cutting edge deep learning methods (Transformers, Graph Neural Networks, etc.)   Wet lab validation of at least 1 AI-driven drug discovery initiatives  Demonstrated experience writing clean, maintainable, production-quality Python code, with examples available in code repositories  Familiarity with MLOps and DevOps best practices   Exposure to distributed computing (Microsoft Azure, HPC Cluster, etc.)   Strong track record of publications of individual research in top-tier AI journals and conferences    Ability to demonstrate business value related to developed AI and Machine Learning solutions in biology and medicinal chemistry related to your modeling efforts  Ability to work effectively in a fast-paced startup environment with evolving projects and shifting priorities driven by business needs  E...