Systems Integration Engineer 4
The University of California, San Diego
About this position
Position Description
UC San Diego is a leading public institution and one of the world’s top 15 research universities, renowned for fostering collaboration, innovation, and societal impact. The School of Physical Sciences, founded by Nobel laureates and National Academy members, includes the Departments of Chemistry and Biochemistry, Mathematics, Physics, and Astronomy & Astrophysics, driving UC San Diego’s global reputation. As one of the largest schools in Academic Affairs, Physical Sciences is led by the Dean, with support from Assistant and Associate Deans, and Department Chairs. The School comprises approximately 200 faculty FTE, 50 professional researchers, 120 postdoctoral scholars, 45 lecturers, 200 staff, and 100 student workers. It serves 4,000 undergraduate majors, 700 graduate students, and enrolls 76,000 students annually. With $184 million in annual expenditures, including $76 million in sponsored research, the School occupies 600,000 square feet across eight buildings, supporting diverse instructional, research, and recharge facilities. The School of Physical Sciences IT (SPS IT) is a cutting-edge federation of service providers, with a core of specialized research IT professionals at its core. Specifically, SPS IT is a mid-sized computing recharge facility organized and managed to provide user-centered, highly collaborative, cost-effective, durable, agile, and innovative solutions for researchers, academics, students, and laboratory staff across the School of Physical Sciences, School of Biological Sciences, and School of Medicine. The Systems Integration Engineer 4 serves as a senior technical authority responsible for architecting, engineering, and managing advanced research computing and systems integration platforms supporting the School of Physical Sciences and partner divisions across the UC San Diego research enterprise. This role designs, implements, and sustains complex, distributed, and multi-tenant infrastructure environments that enable high-performance, data-intensive, and GPU-accelerated scientific workflows across multiple schools, shared facilities, and external collaborators. Operating with a high level of independence, the incumbent oversees a large-scale, geographically distributed research computing ecosystem, including federated CPU and GPU clusters, enterprise storage systems, backup and archival platforms, virtualization and container orchestration environments, and instrument-adjacent data acquisition systems supporting mission-critical scientific workloads.The position leads the design and implementation of scalable, federated compute platforms that complement centrally managed campus resources. These environments support real-time processing, exploratory analysis, workflow development, and specialized scientific applications. Key responsibilities include integrating HPC, workload scheduling, container orchestration, virtualization, CI/CD automation, and infrastructure-as-code practices to deliver secure, scalable, and reproducible environments. The role also includes developing and maintaining end-to-end research data pipelines, including high-speed ingestion, GPU-accelerated processing, and data lifecycle and archival strategies aligned with compliance requirements. The Systems Integration Engineer 4 enables cross-lab collaboration by aligning software environments and data workflows across systems, while providing advanced technical consultation, evaluating emerging technologies, and contributing to strategic planning efforts that enhance the scalability, resilience, and sustainability of research computing infrastructure. Occasional evenings and weekends may be required.
Qualifications
Demonstrated experience in systems integration, infrastructure engineering, or HPC/research computing environments, including designing and supporting complex, distributed systems. Experience designing, implementing, and supporting complex, multi-platform environments (Linux, macOS, Windows), with strong Unix/Linux system administration skills (installation, configuration, patching, security, troubleshooting). Experience with containerization and orchestration technologies (e.g., Docker, Podman, Kubernetes, OKD) in production or research environments. Experience with automation and infrastructure-as-code practices, including tools such as Ansible, GitOps, CI/CD pipelines, and development of automation scripts or system tools. Experience with networking, security, and system monitoring, including firewalls, performance monitoring, and troubleshooting complex, distributed, multi-platform systems. Demonstrated ability to design and implement complex systems integration solutions, including identifying software/hardware interdependencies and developing deployment or implementation plans. Demonstrated experience designing, deploying, and managing ZFS-based storage systems in large-scale research environments, including RAIDZ configurations, snapshotting, replication, performance tuning, and data integrity management. Experience supporting and maintaining Cryo-Electron Microscopy (Cryo-EM) computational environments, including end-to-end workflows for data ingestion, processing, and analysis across GPU-accelerated platforms. Familiarity with tools such as RELION, CryoSPARC, cisTEM, MotionCor2, and associated data pipelines preferred. Experience building and supporting molecular dynamics (MD) software environments, including deployment, optimization, and user support for packages such as GROMACS, NAMD, AMBER, LAMMPS, or similar scientific applications. Experience designing and managing virtualization platforms, including Proxmox VE or comparable hypervisor-based environments, supporting multi-tenant workloads and high-availability configurations. Experience deploying and operating Kubernetes-based platforms, including lightweight or immutable infrastructure distributions such as Talos Linux, with an emphasis on secure, scalable, and reproducible cluster design. Experience integrating high-performance storage, compute, and GPU resources into cohesive research platforms, including support for high-throughput data pipelines and instrument-adjacent workflows. Experience evaluating and integrating new technologies, along with proficiency in scripting or programming (e.g., Python, Bash, C/C++, JavaScript) to support system automation and optimization. Experience supporting instrument-driven data environments (e.g., Cryo-EM, imaging, sequencing) with high-throughput ingestion and near real-time processing requirements. Strong communication and collaboration skills, including the ability to work with technical and non-technical stakeholders, clearly convey complex concepts, and support cross-functional teams. Willingness and demonstrated ability to embrace and consistently uphold the principles of community for a collaborative work environment. Knowledge of University Policies & Procedures preferred. Bachelor’s degree in computer science, Information Technology, or related field, OR equivalent combination of education and relevant experience.
Job Location
Campus