> Markdown version of [/jobs/ext/4601706-staff-software-engineer-hpc](https://www.wearedevelopers.com/jobs/ext/4601706-staff-software-engineer-hpc). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer, HPC - **Company:** Zoox - **Location:** San Mateo, CA, United States - **Salary:** $201,000 - $315,000 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Cloud Computing, Distributed Systems, Job Scheduling, Machine Learning, Software Engineering, Kubernetes, Slurm, Data Generation - **Published:** November 6, 2026 - **Apply:** https://www.juju.com/job/7_19591C99EF9CB5F83BA116A1F53357EA ## About the Role You will work closely with stakeholders in Autonomy and Software teams to understand their workload requirements and translate them into robust, scalable infrastructure.In this role, you will:Design and implement core services and abstractions for distributed compute infrastructure supporting hundreds of thousands of concurrent jobsWork with customer teams and other infrastructure teams to build a multiyear software engineering roadmap for the HPC platformLead multi-quarter, cross team initiatives that drive org-wide improvementsCreate production-grade APIs, SDKs, and tools that make it easy for engineers across Zoox to run large-scale distributed workloadsDesign and improve job scheduling algorithms and auto-scaling policies to maximize reliability and resource availabilityDesign multi-region orchestration strategies that optimize for data locality, reliability, and performanceIdentify and resolve systemic reliability and performance issues through profiling, analysis, and collaboration with workload owners across multiple teamsEvaluate new technologies and paradigms that improve Zoox's computational and storage capabilitiesDevelop capacity planning tools and forecasting models to support Zoox's growing compute needsMentor junior engineers, guiding them through their career developmentQualificationsExperience designing and operating large-scale distributed systems in productionExperience with Ray.io, particularly Ray Core and Ray Data (or equivalent technologies)Experience with Kubernetes, particularly for heterogeneous workloadsExperience with cloud infrastructure on AWS or similar providersTrack record of shipping and operating reliable, highly available scalable infrastructureDemonstrated ability to prioritize development work and build cross-functional consensus around technical tradeoffsProficiency with PythonBonus QualificationsExposure to machine learning workloads (training, inference, data generation)Experience with Kubernetes or SLURM at scale (>10k+