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