⚡DevOps Engineer
🌍Location: San Francisco, CA (On-site)
💲Compensation: $160,000-$225,000 base + strong upside
My 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 Role
We’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 Do
- Own and scale multi-cloud infrastructure across AWS and GCP
- Build and maintain Terraform-based infrastructure across environments
- Design and operate robust CI/CD pipelines
- Manage containerised systems (Docker, Kubernetes)
- Support HPC and GPU compute environments for simulation and ML workloads
- Implement monitoring, observability, and reliability best practices
- Drive security, cost optimisation, and infrastructure governance
What We’re Looking For
- Strong experience with AWS and/or GCP
- Deep Terraform / infrastructure-as-code expertise
- Experience designing and operating CI/CD systems
- Solid understanding of containers (Docker, Kubernetes)
- Strong Linux, networking, and production systems experience
- Comfortable operating in a fast-moving, high-ownership environment
Nice to Have
- Experience with HPC / GPU infrastructure (SLURM, ParallelCluster)
- Background in ML, simulation, or data-intensive systems
- Workflow orchestration tools (Airflow, Dagster, Prefect)
Why This Role
- Work on problems rarely tackled outside government or elite research environments
- Own infrastructure at a foundational level in a small, high-calibre team
- Operate at the intersection of science, ML, and real-world deployment
- Massive scope across cloud, compute, and large-scale data systems
Build the infrastructure powering systems designed to solve some of the most complex real-world challenges at global scale.
