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