Heavy AWS + HPC

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.

===è 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, 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