DevOps Engineer + HPC (High Performance Computing)

DevOps Engineer + HPC (High Performance Computing) is a must with any Pharma/Life science experience.

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.

·         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