Software Engineer, Infrastructure

Exa; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

A leading tech firm in Singapore is seeking infra engineers who will build the underlying tools and infrastructure for their cutting-edge AI search engine. Key responsibilities include developing GPU cluster orchestration and optimizing large-scale systems for performance. Desirable candidates will have experience with GPU clusters, Kubernetes, and an obsession for reliability and efficiency. This role is in-person, with sponsorship available for international candidates.

Qualifications

• Experience designing and operating large-scale infrastructure.
• Obsession with reliability, observability, and optimization.
• Comfort working on production-grade tooling and systems at scale.

Responsibilities

• Build GPU cluster orchestration in Kubernetes.
• Implement map-reduce batchjobs on Ray.
• Develop observability tooling.
• Improve observability across production systems.

Skills

Designing large-scale infrastructure

Operating GPU clusters

Kubernetes clusters

Batchjob systems

Reliability and observability optimization

Tools

Ray

Observability tooling

Kubernetes

Job description

Exa is building a search engine from scratch to serve every AI application. We build massive-scale infrastructure to crawl the web, train state-of-the-art embedding models to index it, and develop super high performant vector databases in Rust to search over it. We also own a $5M H200 GPU cluster that regularly lights up tens of thousands of machines.

Our Infrastructure Team builds the underlying tooling and infrastructure that powers all Exa's systems. Basically, we need more infra engineers to build the machine that builds the machine so that we can move as fast as possible as an engineering org. That could mean building GPU cluster orchestration in Kubernetes, map-reduce batchjobs on Ray, or the best observability tooling in the world.

Desired Experience

• You have experience designing and operating large-scale infrastructure - GPU clusters or large Kubernetes clusters or cloud batchjob systems

• You bring an obsessive mindset — always thinking about reliability, observability, and optimization across the entire stack.

Example Projects

• Build the Kubernetes orchestration on a $20M GPU cluster

• Scale our AWS batchjob system to handle map reduce jobs over 10s of thousands of machines

• Design GPU scheduling software so we max out our cluster utilization

• Build observability into our production systems

This is an in-person opportunity in Singapore. We’re happy to sponsor international candidates.