Heavy AWS + HPC

Zeal Solutions Inc; Charlotte (NC); Remote; USD 120,000 - 180,000; Full time

Job summary

Zeal Solutions Inc. is seeking a DevOps Engineer with strong HPC expertise to design, automate, and maintain compute-focused infrastructure for pharma/ life sciences workloads. The role blends DevOps with HPC cluster management and cloud-based AI/ML support.

You will design scalable cloud infrastructure, work with SLURM/PBS schedulers, and build CI/CD for ML model training and deployment, ensuring secure, cost-efficient operations in a remote US setting.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Proven experience in cloud computing (AWS, Azure, GCP) 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.

Responsibilities

• Design, implement, and manage cloud-based infrastructure that supports AI/ML workloads.
• 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.

Skills

Python

Bash

Docker

Kubernetes

EC2

SLURM

PBS

Terraform

CloudFormation

RHEL

HPC

Git

Education

Bachelor’s degree in Computer Science

Tools

Terraform

CloudFormation

DynaTrace

Job description

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

Client: Pharma Client

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.

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, GCP) 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