Senior Machine Learning Scientist, AI Foundation Model Specialist

We are seeking a passionate and highly skilled Machine Learning Scientist with expertise in Foundation Models to join our core AI research team, focusing on developing and scaling our next-generation foundation models for biology. You will work with domain area experts to explore fundamental research questions at the intersection of deep learning and biology, and apply the latest in AI research to unique, large-scale biological datasets (many terabytes) to develop models that push the state-of-the-art. If you are excited by using your strong ML knowledge to work with others and to solve frontier problems in drug discovery, this is a unique opportunity. Collaborate closely with computational biologists to integrate domain knowledge, define scientifically meaningful tasks, and translate biological challenges into ML frameworks. You will work together to formulate key scientific questions in biology that can be addressed through innovative ML/AI approaches and design computational experiments to test hypotheses. Contribute to, and potentially lead (depending on level) research into novel deep learning architectures, training paradigms (e.g., self-supervised, multi-modal), and algorithms tailored for large-scale biological sequence data and related modalities. Rigorously implement, train, debug, and evaluate models to demonstrate scientific validity and potential for downstream application. Stay current with advancements in both machine learning and computational biology literature, identifying cross-disciplinary opportunities to solve real-world challenges. Contribute to team knowledge sharing and code quality through documentation and code reviews. Share research findings through internal presentations, and potentially external publications or conference presentations.

Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of genome biology to identify novel drug targets, mechanisms, and therapeutics inaccessible through traditional methods. We co-develop drug programs and AI models with partners and internally, and pursue major technology builds with pharmaceutical partners. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team located in Toronto, Cambridge, MA, and select other sites is revolutionizing how new medicines are created.