<p>REQUIRED: Bachelor's degree in the physical/chemical sciences, computer science or related technical field; a minimum of five years of relevant programming experience; fluency and experience in both Python and JavaScript; experience developing web-based single page applications with the Vue 3 Javascript framework and using CSS styling; and familiarity using cloud environments like AWS for development. PREFERRED: a minimum of two years of experience working with scientist/engineers to develop and refine computer codes for application in the physical sciences; experience working with large codebases, containerization, microservices, testing, and continuous integration pipelines; knowledge of PyTorch or other related machine learning code; and familiarity with cheminformatics, chemical synthesis planning, and/or property prediction. Job #24922-9</p> <p>Revised 4/24/2025</p> <p>SOFTWARE DEVELOPER 2, Chemical Engineering, to be responsible for the full cycle, full-stack software development at the Machine Learning for Pharmaceutical Discovery and Synthesis (MLPDS) consortium at MIT. Responsible for continued development and maintenance of a web-based application deploying machine learning models for chemical synthesis planning and property prediction ASKCOS; advancing best practices in close collaboration with research labs through integration of latest machine learning models, design and implementation of new features, as well as continuous improvement for scalability and robustness; writing code in JavaScript (Vue 3), Python, bash, styling in css, and other languages as necessary; maintaining and improving a modern front-end web application to set up parameters for, and view the results from, machine learning predictions for chemical compounds; maintaining and improving a microservice-based backend infrastructure including the API gateway and various ML prediction services; working with students and post-docs to integrate research products (code and models) into the web application to make them easily accessible to users; and working on modernization and professionalization of existing code to improve code quality, maintainability, and performance through profiling, logging, and refactoring as appropriate.</p>