"Software Developer"

SOFTWARE DEVELOPER 2

Chemical Engineering (ChemE)-Machine Learning for Pharmaceutical Discovery and Synthesis (MLPDS) Consortium, to support the development, deployment, and operation of machine learning–enabled software systems for research and engineering applications. Will work closely with faculty, researchers, and graduate students to translate scientific and engineering workflows into robust, scalable, and reproducible computational applications. Will focus on backend software development, cloud-based deployment, and the management of machine learning applications in containerized and Kubernetes-based environments.

Responsibilities include Software and Machine Learning Development of machine learning models using established frameworks such as PyTorch and PyTorch Lightning; Cloud Infrastructure and Containerization using Docker and Kubernetes, with a primary focus on AWS Elastic Kubernetes Service (EKS); design and maintain continuous integration and continuous deployment (CI/CD) pipelines to automate testing, validation, and deployment of research software; and support reproducible build and deployment processes consistent with academic and research best practices. Will implement and maintain application and infrastructure monitoring using tools such as Prometheus and Grafana; collect and analyze application usage and performance metrics using platforms such as Google Analytics or comparable tools; and assist in diagnosing and resolving software and infrastructure issues affecting research applications.

Job Requirements

REQUIRED: Bachelor’s degree in Computer Science, Chemical Engineering, Chemistry, or a closely related discipline; a minimum of five years of relevant programming experience; demonstrated experience programming in Python, JavaScript, and Bash. Practical experience with Docker and Kubernetes, including deployment on AWS EKS; experience deploying and managing Kubernetes applications using Helm; proficiency in Kubernetes tooling, including Lens for app/cluster management; proficiency with Git and collaborative development workflows (GitHub and/or GitLab); experience developing and maintaining CI/CD pipelines; experience with one or more machine learning frameworks including PyTorch; experience developing backend software, including asynchronous or distributed processing systems; and familiarity with application and infrastructure monitoring tools such as Prometheus and Grafana.

PREFERRED: Familiarity with RDKit or other cheminformatics or molecular modeling libraries; experience supporting computational research or research software platforms; experience working in interdisciplinary academic or research environments; and familiarity with best practices for research data management and open-source development.