Hpc Architect

Location:Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world.Responsibilities:Hybrid Architecture Design: Architect and deploy scalable HPC clusters usingon-prem and/or cloud-native HPC cluster managers (e.g., AWS ParallelCluster + Amazon EC2 / Azure CycleCloud + Azure VM Scale Sets / Google Cloud Cluster Toolkit or similar + Compute Engine), ensuring seamless integration with on-premises schedulers.Proven expertise with HPC schedulers and orchestration patterns (e.g., Slurm, cloud HPC cluster orchestration, batch orchestration)Design and optimize data architectures for large-scale HPC workloads, including high-throughput data movement between on-premises and cloud environments and integration with parallel file systems.Ensure data access, lifecycle, and reproducibility patterns to support scientific computing performance and operational requirements.Design and implement high-performance networking solutions, includingprivate dedicated connectivity and low-latency HPC interconnects(e.g., AWS Direct Connect / Azure ExpressRoute / Google Cloud Interconnect; AWS EFA / Azure HPC fabrics e.g. IB/ GCP HPC interconnect options etc.), to support low-latency MPI applications.Design high I/O workloads (parallel file system patterns) (e.g., AWS / GCP / Azure Managed Lustre or parallel FS deployments and/or self-managed Lustre/GPFS/BeeGFS), observability, reproducibility and operational excellenceDefine and maintain containerization standards using containerization and related technologies to ensure binary compatibility across heterogeneous hardware and environments.What we expect:Knowledge of HPC-with-cloud integration strategies, experience with technical feasibility planningStrong understanding of regulated enterprise R&D environmentsUnderstanding scientific computing reproducibility requirements, relying on enterprise standard tooling.Deep understanding of Amazon VPC /Google Cloud / Azure networking, peering and security group configurations.Nice to have:Experience in life-sciencesExperience in specific applications in life sciences, Jupyter, MatlabWe offer:Competitive compensationRemote or office workHealthcare benefits: medical insurance and paid sick leaveContinuous education, mentoring, and professional development programs#J-*****-Ljbffr

Knowledge of HPC-with-cloud integration strategies, experience with technical feasibility planning Strong understanding of regulated enterprise R&D environments Understanding scientific computing reproducibility requirements, relying on enterprise standard tooling. Deep understanding of Amazon VPC /Google Cloud / Azure networking, peering and security group configurations. Nice to have: Experience in life-sciences Experience in specific applications in life sciences, Jupyter, Matlab

Competitive compensation Remote or office work Healthcare benefits: medical insurance and paid sick leave Continuous education, mentoring, and professional development programs #J-*****-Ljbffr