Heavy AWS + HPC + Parallel Cluster + Slrum

Heavy AWS + HPC High Performance Computing, Parallel Cluster * Slrum is a must

Location: US, Remote

We're seeking a DevOps Engineer with High Performance Computing (HPC) expertise to design, automate, and maintain the infrastructure supporting the compute-intensive scientific and research workloads (e.g., genomics, molecular modeling, drug discovery simulations). This role bridges traditional DevOps practices with specialized HPC cluster management in a life sciences/pharma environment.

Cloud Systems Engineer (AI/ML & HPC Specialization)

Key Responsibilities:

• Design, implement, and manage cloud-based infrastructure that supports AI/ML workflows. for
• Collaborate with data scientists and ML engineers to deploy scalable machine learning models into production.
• Ensure the security, scalability, and reliability of AI/ML systems in the cloud.
• Optimize cloud resources for cost-effective and efficient use.
• Stay current with the latest in cloud services, AI/ML tools, and industry best practices.
• Provide technical leadership and guidance in cloud and AI/ML architecture.
• Develop and maintain CI/CD pipelines for AI/ML model training and deployment.
• Monitor and troubleshoot AI/ML applications and cloud environments.
• Document system design and operational procedures.
• Collaborate with AI/ML and HPC teams to understand their computing and storage needs.

Qualifications:

• Bachelor s or Master s degree in Computer Science, Engineering, or related field.
• Proven experience in cloud computing (AWS, Azure, Google Cloud Platform) and cloud architecture.
• Strong background in AI/ML technologies, with experience in deploying ML models.
• Proficiency in scripting languages (Python, Bash) and containerization technologies (Docker, Kubernetes).
• Proficiency with virtual compute environments (EC2).
• Hands-on experience with High Performance Computing (HPC) and server node Cluster Management
• Strong Knowledge of Linux/Unix operating systems (RHEL/Ubuntu)
• Experience with job schedulers (like SLURM, PBS), resource management, and system monitoring tools (DynaTrace).
• Understanding of storage solutions and file systems used in HPC (such as Lustre, GPFS).
• Experience with infrastructure as code (IaC) tools like Terraform or CloudFormation.
• Knowledge of networking, security, and database technologies in a cloud environment.
• Excellent problem-solving, communication, and team collaboration skills.

Preferred Skills:

• 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).
• Operational experience running large scale platforms, including AI/ML platforms