Software and Infrastructure Engineer

The Scientific Computing Core (SCC) is the technical backbone of the Flatiron Institute. SCC develops, deploys and maintains computational infrastructure from supercomputers to desktop workstations and provides resources, services, and expertise to the Institute's research community. We are seeking a Software and Infrastructure Engineer who is passionate about technology, innovation, and science to join the team in maintaining and growing Flatiron's research computing resources.

They will work in the deployment, operation and maintenance of the Flatiron Institute’s Scientific computing service infrastructure both on prem and in the cloud, and support scientific applications in the Flatiron Institute scientific computing centers. This is a full-time position based in Simons Foundation’s offices in New York City.

• Develop, deploy and maintain software, services and tools that support scientific computing and data-intensive research.
• Work with scientists to translate research requirements into practical software, cloud and infrastructure solutions.
• Support and troubleshoot scientific applications and workflows across Linux, cloud, containerized and distributed computing environments.
• Diagnose performance, reliability and resource-utilization issues and optimize computational workloads.
• Develop automation, APIs and operational tools that improve deployment, monitoring and efficiency.
• Support reproducible scientific workflows involving large datasets, machine learning, GPUs or other advanced computing technologies.
• Evaluate and adopt appropriate emerging technologies for scientific applications.
• Collaborate across scientific, software engineering and infrastructure teams and contribute to documentation and knowledge sharing.
• Perform other duties or tasks as assigned or required.

Education Bachelor's degree in computer science, engineering, computational science, mathematics, physics, neuroscience, biology or a related technical or scientific field, or equivalent professional experience. Experience 2 to 5 years of professional software engineering, cloud engineering, research computing, scientific computing or related experience. Relevant research and substantial technical project experience may also be considered. Demonstrated experience developing and maintaining production software or cloud-based services.

Strong programming experience in Python and experience with one or more additional languages such as Go, Java, C++, C# or similar. Practical experience working in Linux environments. Experience with cloud computing platforms such as AWS, Google Cloud Platform or Microsoft Azure. Experience with containers and containerized application environments, including Docker; familiarity with Kubernetes or similar orchestration technologies is highly desirable.

Experience diagnosing software and infrastructure problems across applications, services, operating systems, networks or computing environments. Experience with performance analysis, resource utilization, reliability or optimization of production or computational workloads. Experience developing automation, APIs, services or tools that improve operational efficiency and reduce manual processes. Experience with scientific computing, computational research, biological data, neuroscience, machine learning or another data-intensive scientific domain is desirable but not required.

Experience applying computing to scientific, research or data-intensive problems is desirable.

Strong software engineering skills, including experience developing maintainable, tested and documented software. Strong working knowledge of…