Senior High Performance Computing Engineer

design, integration, and management of High-Performance Computing (HPC) systems

Roles & Responsibilities

• Implement and manage

  cloud-based infrastructure

  that supports

  HPC environments

  for data science (e.g., AI/ML workflows, Image Analysis).
• Collaborate with data scientists and ML engineers to deploy scalable

  machine learning models into production

  .
• Ensure the

  security, scalability, and reliability

  of HPC systems in the cloud.
• Optimize cloud resources for

  cost-effective and efficient use

  .
• Keep abreast of the latest in

  cloud services and industry standard processes

  .
• Provide

  technical leadership and guidance

  in cloud and HPC systems management.
• Develop and maintain

  CI/CD pipelines

  for deploying resources to multi-cloud environments.
• Monitor and fix cluster operations/applications and cloud environments.
• Document system design and operational procedures.

What We Expect of You

proactive and technically adept

Basic Qualifications

• Master's degree with 4-6 years of experience in Computer Science, IT, or a related field with hands-on

  HPC administration

  OR

• Bachelor's degree with 6-8 years of experience in Computer Science, IT, or a related field with hands-on

  HPC administration

  OR

• Diploma with 10-12 years of experience in Computer Science, IT, or a related field with hands-on

  HPC administration

• Demonstrable experience in

  cloud computing

  (preferably AWS) and cloud architecture.
• Experience with

  containerization technologies

  (Singularity, Docker) and cloud-based HPC solutions.
• Experience with

  infrastructure-as-code (IaC) tools

  such as Terraform, CloudFormation, Packer, Ansible, and Git.
• Expert with scripting (

  Python or Bash

  ) and

  Linux/Unix system administration

  (preferably Red Hat or Ubuntu).
• Proficiency with

  job scheduling and resource management tools

  (SLURM, PBS, LSF, etc.).
• Knowledge of

  storage architectures and distributed file systems

  (Lustre, GPFS, Ceph).
• Understanding of

  networking architecture and security best practices

  .

Preferred Qualifications

• Experience supporting research in

  healthcare life sciences

  .
• Experience with

  Kubernetes (EKS)

  and service mesh architectures.
• Knowledge of

  AWS Lambda

  and event-driven architectures.
• Exposure to

  multi-cloud environments

  (Azure, GCP).
• Familiarity with

  machine learning frameworks

  (TensorFlow, PyTorch) and data pipelines.

• Certifications in cloud architecture

  (AWS Certified Solutions Architect, Google Cloud Professional Cloud Architect, etc.).
• Experience in an

  Agile development environment

  .
• Prior work with

  distributed computing and big data technologies

  (Hadoop, Spark).

Professional Certifications (Preferred)

• Red Hat Certified Engineer (RHCE) or Linux Professional Institute Certification (LPIC)
• AWS Certified Solutions Architect - Associate or Professional

Soft Skills

• Strong analytical and problem-solving skills.
• Ability to work effectively with global, virtual teams.
• Effective communication and collaboration with cross-functional teams.
• Ability to work in a fast-paced, cloud-first environment.