Staff Infrastructure Engineer — Production AI & Scale

Warp; South San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Warp Sciences is seeking an Infrastructure and Systems Engineer to design, build, and operate the foundation for production AI workloads. You will work across core infrastructure, data systems, and the training and inference stack, balancing performance, reliability, cost, and speed.

You’ll own production reliability with observability, capacity planning, and incident response, while collaborating with AI researchers to turn experiments into dependable systems.

Qualifications

• Must have built and operated production systems at scale.
• Strong fundamentals in distributed systems, Linux, networking, storage, concurrency, and performance.
• Hands-on experience with AI training and inference workloads, including GPU infrastructure.
• Ability to profile systems and deliver measurable improvements.

Responsibilities

• Design, build, and operate infra for large-scale AI training and inference.
• Build reliable data infrastructure for ingestion, processing, storage, and delivery to workflows.
• Optimize GPU utilization, training performance, latency, throughput, and costs.
• Own production reliability through observability, capacity planning, and incident response.
• Improve deployment, orchestration, and developer tooling for speed.

Skills

Distributed systems

Linux

Networking

Performance engineering

AI workloads

Observability

Ownership and accountability

Tools

Cloud infrastructure

Container orchestration

Infrastructure as code

Job description

Warp Sciences is seeking an Infrastructure and Systems Engineer to design, build, and operate the foundation for production AI workloads. You will work across core infrastructure, data systems, and the training and inference stack, balancing performance, reliability, cost, and speed.

You’ll own production reliability with observability, capacity planning, and incident response, while collaborating with AI researchers to turn experiments into dependable systems.