NCUVO Senior Scientific Software Engineer

The National Connectomics and Ultrastructure Volume Observatory (NCUVO) seeks a Senior Scientific Software Engineer to lead development of the computational backbone for a new, NSF-funded high-throughput volume electron microscopy (htvEM) observatory. This role will connect advanced microscopy with petabyte-scale distributed computing, machine learning, visualization, and data stewardship to make complex connectomics and ultrastructure datasets usable by a broad research community. The successful candidate will architect and optimize scalable CPU/GPU workflows; evaluate and integrate open-source tools; develop new software when existing solutions are insufficient; establish rigorous engineering and validation practices for both manual and frontier model-based software development; and collaborate with scientific and computing partners at UVM and nationally. This is a senior individual-contributor role for an expert who can translate emerging research methods into dependable production systems, and convene collaborative technical activities such as NCUVO hackathons. The position will report directly to the NCUVO Director and will have functional supervision of technical staff. The successful candidate will be a recognized expert in the field who is expected to liaise with external partners in the National Center for Microscopy and Imaging Research (NCMIR), the University of California San Diego (UCSD), and the San Diego Supercomputer Center (SDSC), and with developers of open-source software components used in the NCUVO pipeline.

• PhD in engineering, computer science, biomedical engineering, computational science, data science, neuroscience, physical science, or a closely related field, and at least 10 years of related experience in scientific software engineering, research-computing, microscopy data processing, or an equivalent combination of advanced education and relevant experience.
• Expert knowledge and at least ten years of experience managing and processing large microscopy datasets in the approximately 100-terabyte to 1-petabyte range using large-scale distributed computing environments. Experience with electron microscopy or volume electron microscopy is strongly preferred.
• Demonstrated experience independently architecting, developing, deploying, integrating, and sustaining modular production software and custom pipeline components for specialized research needs across complex computing environments.
• Demonstrated experience with high-performance or distributed computing, including parallel CPU and GPU workflows, and with profiling and optimizing runtime, memory, storage, input/output, and network performance for very large datasets.

• Advanced programming experience in Python and at least one compiled or numerical language such as C, C++, or MATLAB in a Linux environment. Experience with collaborative software-engineering practices, including version control, testing, code review, documentation, release management, and reproducible workflows.

• Demonstrated experience with machine learning and image processing, including alignment, registration, segmentation, feature detection, or comparable computer-vision problems.
• Demonstrated ability to use frontier AI models effectively and responsibly to support development of maintainable, reliable, testable, and extensible software or pipeline components.
• Demonstrated ability to evaluate emerging software from the research community; reproduce or validate relevant results; assess fitness for scientific and production use; and deploy appropriate components within a supported software environment.
• Demonstrated ability to investigate and resolve undefined, highly complex technical problems; work autonomously with high-level direction; establish technical plans and standards; and coordinate and influence work across institutional, scientific, technical, vendor, and external partner groups.
• Demonstrated experience providing technical leadership, guidance, coaching, or mentoring to staff, students, or other contributors. Experience planning and facilitating collaborative technical-development events such as hackathons, code sprints, or design workshops. Effective written and oral communication skills., Extensive experience with serial-section or volume electron microscopy, connectomics, petabyte-scale scientific imaging, ground-truth annotation and model evaluation, scientific visualization, research publications, open-source scientific software, commercial segmentation services, and multi-institutional team science.