Member of Technical Staff - Infrastructure
South San FranciscoFull-timePosted 4d ago
About the role
Infrastructure and systems engineer to build the foundation for production AI workloads, spanning core infrastructure, data systems, and the training/inference stack for large-scale AI workloads in production.
Responsibilities
- Design, build, and operate infrastructure for large-scale AI training and inference.
- Design & build reliable data infrastructure for ingestion, processing, storage, and delivery to training and evaluation workflows.
- Optimize GPU utilization, distributed training performance, inference latency and throughput, and infrastructure cost.
- Optimize data storage, and access for training and inference.
- Own production reliability through observability, capacity planning, incident response, and recovery.
- Improve deployment, orchestration, and developer tooling so engineers and researchers can move quickly.
- Partner with AI engineers and researchers to turn experimental workloads into dependable production systems.
- Diagnose bottlenecks across compute, networking, storage, data pipelines, and model execution.
Qualifications
- A demonstrated track record of designing, shipping, and operating production systems at scale, with ownership beyond the initial launch.
- Strong fundamentals in distributed systems, Linux, networking, storage, concurrency, and performance engineering.
- Experience building and operating cloud infrastructure, container orchestration, and infrastructure as code.
- Experience with data infrastructure, including distributed processing, pipelines, and storage systems.
- Hands-on experience supporting and optimizing AI training and inference workloads, including GPU infrastructure and distributed execution.
- The ability to profile systems, identify bottlenecks, and deliver measurable improvements in performance, reliability, or cost.
- An AI-native approach: comfortable working closely with model teams, understanding how AI workloads behave, and using AI tools effectively in your own engineering workflow.
- Strong ownership, clear communication, and sound judgment when requirements are ambiguous.
Skills
Required:Distributed systemsLinuxNetworkingStorageCloud infrastructureContainer orchestrationInfrastructure as codeAI training/inference workflows
Last updated Oct 22, 2026. Interested? Apply on the company site.
About Warp Sciences
Warp Sciences | AI and robotics for faster drug discovery
Warp is the U.S. chemistry CRO helping scientists discover new medicines faster. We bring expert chemists, AI, and robotics together to make the molecules research teams need—and build automated labs that learn from every experiment.
AIroboticsdrug discoverychemistry CROautomation
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