Master's degree or equivalent work experience in Computer Science, Physics, Engineering, Chemistry, Mathematics or a related field.
Strong familiarity with Linux, git and the open-source ecosystem.
Proficient experience working with research software, large datasets, and databases.
Experience building and maintaining cloud infrastructure (e.g., Azure).
Experience building processing pipelines and web apps in Python.
Strong analytical, problem-solving, and communication skills.
Passionate about pushing the boundaries of science. Prior experience developing high-performance scientific software is not required, but preferred.
Responsibilities
Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data.
Build and maintain model evaluation pipelines and web apps.
Design, implement, and support tools and technologies that enable the development, deployment, and scaling of machine learning applications.
Collaborate with cross-functional teams, including scientists, researchers, and software engineers.
Document and share best practices across the organization.
Maintain the highest standards in code quality and software design.