Roles & Responsibilities:

Implement, and manage cloud-based infrastructure that supports HPC environments that support 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.

Basic Qualifications:

Master's degree with a 4 - 6 years of experience in Computer Science, IT or related field with hands-on HPC administration OR
Bachelor's degree with 6 - 8 years of experience in Computer Science, IT or related field with hands-on HPC administration OR
Diploma with 10-12 years of experience in Computer Science, IT or 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 (please mention if the certification is preferred or mandatory for the role):
Red Hat Certified Engineer (RHCE) or Linux Professional Institute Certification (LPIC)
AWS Certified Solutions Architect – Associate or Professional

Senior High Performance Computing Engineer