HPC Engineer - Privacy Research Program

solutions to current challenges and creative, sustainable new approaches as technologies and university priorities evolve. We are a community of problem-solvers, innovators, and stewards of trust who take pride in building technology foundations that are reliable, secure, and designed for the future. We bring together technology expertise across academic, clinical, infrastructure, operations, research, and student domains, applying our knowledge of digital transformation and effective user experiences. Guided by our core values of innovation, integrity, collaboration, optimism, supporting success, and community-centered service, we?re not just maintaining technology-we?re shaping how it enables discovery, connection, and impact across the university and beyond. What You'll Do The High Performance Computing Engineer is responsible for designing, developing, and deploying high-performance computing systems and applications. This role provides technical guidance in the installation, configuration, and maintenance of HPC systems and tools. This HPC Engineer position will be focused on building and deploying the new services and infrastructure needed to support a secure and compliant research computing environment as part of the Privacy Program and Secure Research Computing Development Project. This is a two-year limited-term appointment with possibility of extension. HPC Systems Engineering: Build and deploy the new secure, compliant, services within the research computing ecosystem as identified as part of the Privacy Program and Secure Research Computing Development Project. Integrate these new user facing services into our existing HPC web gateways such as Open OnDemand, Jupyter Notebooks and RStudio. Install, maintain and test open source and commercial software as needed for the new services being built in this project. Utilize configuration management, infrastructure as code, and security best practices for all project work. Document all work and provide regular progress updates. Work closely with other RT and TTS technical staff to ensure new services are part of a cohesive plan. This includes network, storage administration, virtualization layer and firewall issues. Respond to outage, emergency or urgent issues as needed. HPC Systems Innovation and Consultation: Provide system administration services and consult with other team members to evaluate Proof of Concept (POC) systems to foster innovative architectures and solutions in the selection of the new software and hardware components needed for this project. Service Management, Education, Outreach: Maintain ties with the larger system administration and research computing community to better understand the paradigms, methods, and opportunities others are using to solve the problems identified in this project. Successful TTS staff are known for effectively applied expertise, continuous learning, thoughtful attention to detail, timely and appropriately calibrated follow-up, proactive and constructive problem solving, openness to new approaches, and for building effective partnerships and trust within TTS, across the university, and (where relevant) with external partners. All TTS staff are expected to follow departmental shared administrative practices, including effective planning and communication around time off, attending required TTS and university trainings, and developing professional goals as part of the PDP planning process. TTS staff are also responsible for working in ways that align with the TTS vision statement and for being aware of and following individual group and department-wide shared practices. What We're Looking For Basic Requirements: Knowledge and experience typically acquired by: Bachelor's Degree Knowledge and experience typically acquired through in science High School Diploma plus 8 or more years related experience in a higher education, research, scientific or technical computing environment Understanding of and experience with high performance computing, scientific gateways from both an architecture, subsystems and networking perspective as well as daily usage, support, and application-level knowledge. Demonstrated experience maintaining the specific technologies used in research and high-performance computing such as job schedulers (Slurm), Containers (singularity, docker), RDMA over ethernet, Infiniband, GPUDirect, etc. Extensive experience with scripting (e.g., Shell, Batch, Perl, Python, etc.). Broad experience installing, maintaining open source or commercial research computing web gateway solutions such as OpenOnDemand. Strong experience installing, configuring, maintaining, troubleshooting common frameworks and software used in research and high-performance computing such as scikit-learn, TensorFlow/TensorBoard, Keras, Theano, Caffe, Pytorch, MXNet, DGL, GPU libraries such as NVIDIA RAPIDS suite (cuDF, cuML, cuGraph, cuDNN). on both GPU and CPU architectures. Management/monitoring frameworks such as DCGM. Broad experience and resourcefulness with all aspects of the system management and development cycle from analysis through evaluation and documentation when approaching system engineering challenges. Proficiency with modern system administration devops and design patterns to automate Linux HPC clusters, operating system, software installation via scripting as well as configuration management systems such as Ansible and Warewulf. Willing and able to learn technologies and required domain knowledge at a rapid pace. Background supporting academic researchers (e.g., faculty, staff, students, etc.). Strong communication, presentation, customer service, problem-solving skills in pursuit of system management and innovation. Demonstrated ability to work effectively in a dynamic, collaborative environment with colleagues and build partnerships across technical disciplines, job functions and departments. Dedication to taking ownership of projects that include identifying problems, developing testing protocols, and developing and implementing solutions. Preferred Qualifications: Master's Degree science or engineering field plus 2 or more years related experience in a higher education, research, scientific or technical computing environment. Familiarity and experience with resources at private or public sector HPC research computing environments or national centers beneficial. Familiarity and experience with running HPC workloads in cloud computing environments. Experience deploying or working with NIST 800-171 or CMMC compliant research computing environments. Knowledge of the continuum of research computing and scalability from desktop to HPC, cloud and national centers. Pay Range Minimum $89,100.00, Midpoint $111,500.00, Maximum $133,800.00 Salary is based on related experience, expertise, and internal equity; generally, new hires can expect pay between the minimum and midpoint of the range.