DevOps Engineer

⚡DevOps Engineer🌍Location: San Francisco, CA (On-site)💲Compensation: $160,000-$225,000 base + strong upsideMy client is an early-stage, well-backed deep tech company, building an end-to-end platform spanning advanced modelling, environmental sensing, large-scale simulation, and real-world engineering systems, aiming to convert cutting-edge research into deployable, operational capability.The team brings together expertise across machine learning, atmospheric science, high-performance computing, aerospace systems, and software engineering. Despite being a lean, high-calibre team, they are operating at a level of ambition typically associated with national labs and large-scale research programmes.The RoleWe’re looking for a DevOps Engineer to own the infrastructure layer underpinning the entire platform. You’ll be responsible for building and scaling the cloud, compute, and deployment systems that enable a deeply technical team to operate with the velocity and leverage of a much larger organisation.What You’ll DoOwn and scale multi-cloud infrastructure across AWS and GCPBuild and maintain Terraform-based infrastructure across environmentsDesign and operate robust CI/CD pipelinesManage containerised systems (Docker, Kubernetes)Support HPC and GPU compute environments for simulation and ML workloadsImplement monitoring, observability, and reliability best practicesDrive security, cost optimisation, and infrastructure governanceWhat We’re Looking ForStrong experience with AWS and/or GCPDeep Terraform / infrastructure-as-code expertiseExperience designing and operating CI/CD systemsSolid understanding of containers (Docker, Kubernetes)Strong Linux, networking, and production systems experienceComfortable operating in a fast-moving, high-ownership environmentNice to HaveExperience with HPC / GPU infrastructure (SLURM, ParallelCluster)Background in ML, simulation, or data-intensive systemsWorkflow orchestration tools (Airflow, Dagster, Prefect)Why This RoleWork on problems rarely tackled outside government or elite research environmentsOwn infrastructure at a foundational level in a small, high-calibre teamOperate at the intersection of science, ML, and real-world deploymentMassive scope across cloud, compute, and large-scale data systemsBuild the infrastructure powering systems designed to solve some of the most complex real-world challenges at global scale.