Technical Computing Engineer

Essential Duties and Responsibilities
System Architecture and Design
Develop and design HPC infrastructure: Select, design, and implement HPC systems, including
compute clusters, storage networks, and high-speed interconnects, to meet the varied computational
needs of the research community.
Evaluate and integrate new technologies: Stay abreast of advancements in HPC, cloud computing,
and storage technologies. Evaluate the potential benefits of new technologies and integrate them
into the existing HPC ecosystem to enhance performance and capabilities.
System Administration and Maintenance
Manage HPC resources: Perform system administration tasks on HPC clusters, including
configuration, maintenance, and troubleshooting of hardware, software, and networking components.
Optimize system performance: Monitor system performance, identify bottlenecks, and implement
optimizations to ensure efficient utilization of HPC resources.
Ensure system security: Implement and maintain security measures to protect sensitive data and
computing resources from unauthorized access and cyber threats.
User Support and Collaboration
Provide technical support and training: Assist researchers with technical issues related to HPC
usage. Organize training sessions and workshops on HPC best practices, programming, and
optimization techniques.
Collaborate on research projects: Work closely with research groups to understand their
computational requirements and assist in developing efficient computational strategies, code
optimization, and parallelization.
Software and Application Management
Install and manage scientific software: Deploy and maintain a wide range of scientific applications,
libraries, and development tools on HPC systems to support research activities.
Develop custom tools and scripts: Write custom scripts and tools to automate common tasks,
improve system management, and facilitate complex computational workflows.
Research and Development
Stay informed about the latest research in HPC and related fields.
Data Management and Storage
Implement data management policies: Develop and enforce data storage, backup, and archiving
policies to ensure data integrity and availability.
Optimize data storage and access: Design and maintain scalable storage solutions that provide fast
and efficient access to large datasets, integrating with HPC compute resources.
Preferred Requirements
Education – Master's in Computer or Computational Science, Statistics, or Engineering program.
Experience – Twelve years of experience in HPC related to hands-on system administration and management of
large-scale supercomputing clusters at all levels, the use of parallelization techniques, the use of programming
languages, tools, and techniques with Fortran, C/C++, Java, or POSIX threads, etc., and mass storage
architecting and planning.
Five years of management and leadership experience in HPC or research computing centers.
Experience with computing clusters in Windows and Linux and virtualized environments.
Ability to evaluate and benchmark cluster architectures and their key subsystems (e.g., mass storage,
interconnect, processor technology). Knowledge of scripting languages like Bash, Python, and Perl to
maintain HPC systems and scientific computing. Knowledge of C/C++, Fortran, CUDA, OpenCL,
OpenMP, and MPI for scientific computing. Configuration management tools include Puppet, Chef,
Ansible, Salt, etc. Knowledge of container technologies such as Docker, Singularity, and Kubernetes.C++, Cluster computing, Python Scripting, System Architecture, System Administration