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11 mo agofound 7 d ago

Infrastructure Engineer

Relace·San Francisco·via ashby
mid2+ yrsFull timeawsazuregcpgpuml
What the posting is about

Design and operate high-performance inference and training infrastructure. Collaborate with research and product teams to ensure models run at scale with reliability, speed, and cost-efficiency. Build and scale the backbone of modern code generation.

Read out of the posting
Levelmid
Experience asked2+ years
EmploymentFull time
LocationSan Francisco
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2025-10-29
Found viaashby, direct from their system

We saw it 11 months after it went up.

The posting, as the company wrote it
About Us Relace is building the models and infrastructure that code agents reach for. We power the fastest model on OpenRouter (10,000 tok/s) and deliver optimized small language models designed for retrieval, application, and core code generation functions. Our technology supports some of the world’s fastest-moving companies — including Lovable, Figma, and Vercel — as they deploy and scale code generation to hundreds of millions of users. We recently raised our Series A from a16z, and we’re growing quickly. Our team is made up of mathematicians, physicists, and computer scientists who are deeply passionate about their craft. If you thrive on ambitious technical problems, care about elegant systems design, and want to build the foundation of how code gets written at scale, this is the place for you. The Role As an Infrastructure Engineer at Relace, you’ll design and operate the systems that power our high-performance inference and training infrastructure. You’ll work closely with our research and product teams to ensure our models run at scale with reliability, speed, and cost-efficiency. This is a hands-on engineering role where you’ll shape how we build and scale the backbone of modern code generation. You’ll have the opportunity to: - Architect and manage the infrastructure powering our ultra-fast inference and training stack. - Build reliable, efficient systems for deploying and scaling ML workloads globally. - Work on GPU scheduling, distributed systems, and high-performance cloud deployments. - Optimize performance and cost across compute, networking, and storage layers. - Collaborate with world-class engineers to push the limits of what small models can do. Requirements 2+ years of experience writing high-quality production code Strong experience with cloud infrastructure (AWS, GCP, Azure, or equivalent) Experience with data science and systems optimization Familiarity with ML infrastructure, GPU’s, etc. a plus Work out of our SF office in FiDi

Copied from Relace’s own board, not rewritten. Original ↗

Also open at Relace

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