---
title: 'Infrastructure Engineer at Relace'
canonical: 'https://feeny.ai/job/infrastructure-engineer-relace-san-francisco-zf8xjm22pchz'
type: 'job'
last_seen: '2026-09-11'
---

# Infrastructure Engineer at Relace

- **Company:** Relace
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-10-29
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/relace/4c882256-0667-433b-8ffa-2ebf99a0f7ce

## Job description

## 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

## About Relace

## Company Overview
- **One-liner**: Relace builds specialized AI models and infrastructure for coding agents, enabling fast, cheap, and reliable code retrieval and merging.
- **Entity Type**: Private (startup; Y Combinator Winter 2023)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2022
- **Founders**: Preston Zhou and Eitan Borgnia

## Core Business
- **Primary industry**: AI infrastructure for software development (coding agents, code generation)
- **Target customers**: B2B – AI codegen startups, engineering teams, and enterprises integrating autonomous coding agents into their workflows.
- **Mission**: Build the models and infrastructure to make coding agents a seamless part of all software systems – turning static SaaS pages into malleable user-driven interfaces.

## Products & Services
- **Instant Apply**: A universal code merging model that applies file edits at >10,000 tokens per second (end-to-end latency ~900ms). Reduces token usage by ~40% compared to full-file rewriting with frontier LLMs. [relace.ai](https://relace.ai/)
- **Embedding + Code Reranker**: Semantic search that retrieves relevant context from million-line codebases in ~1–2 seconds, cutting input token usage by over 50% and improving generation quality. [ycombinator.com](https://www.ycombinator.com/companies/relace)
- **Source Control for Agents**: Lightweight push/pull operations, fast branching for subagents, automatic indexing for two-stage retrieval, and rate limits designed for high throughput. [relace.ai](https://relace.ai/)
- **Self-Hosted / VPC Deployments**: On-premise or VPC-isolated deployments for teams with strict compliance or latency requirements. [relace.ai](https://relace.ai/)

## Market Standing
- **Valuation**: Not publicly disclosed (latest round: $23M raised as of Oct 2025 per YC news) [ycombinator.com](https://www.ycombinator.com/companies/relace)
- **Key Metric**: Total funding – $23M (announced October 2025)
- **Notable Investors/Partners**: Y Combinator (Winter 2023 batch), plus production partnerships with Lovable, Magic Patterns, Codebuff, Create, Tempo Labs, and 20+ other AI codegen startups. [ycombinator.com](https://www.ycombinator.com/companies/relace)
- **Growth Signals**: Models running millions of times per week in production; SOC 2 compliant; team of 7 (as of YC profile); hiring across multiple roles (ML, engineering, GTM). [builtin.com](https://builtin.com/company/relace)

## Competitive Advantages
- **Purpose-built SLMs**: Unlike general-purpose LLMs, Relace trains specialized small language models (SLMs) for retrieval and merging – achieving order-of-magnitude improvements in latency and cost without sacrificing accuracy. [relace.ai](https://relace.ai/)
- **Co-optimized infrastructure**: Models and infrastructure are designed together for coding agent workflows, enabling 10k+ tok/s merging and sub-second codebase search. [ycombinator.com](https://www.ycombinator.com/companies/relace)
- **Strong adoption**: Already integrated by leading AI codegen platforms, proving real-world performance and reliability.

## Strategic Focus
- **Expand model capabilities**: Continue training specialized SLMs for additional coding agent tasks (e.g., debugging, testing).
- **Deepen enterprise readiness**: Self-hosted/VPC deployments and SOC 2 compliance signal a push into larger, compliance-sensitive customers.
- **Build the “rails for software on-demand”**: Enable coding agents to be embedded into any software system, making interfaces malleable and user-driven.

## Why Work Here
- **Culture**: In-person team in San Francisco; described as “ex-academics, founders, and hackers” who are “stubbornly optimistic” about solving hard technical problems. [relace.ai/about-us](https://relace.ai/about-us)
- **Work policy**: In-office (San Francisco) with a hybrid workspace option for some roles. [builtin.com](https://builtin.com/company/relace)
- **Engineering focus**: High agency, early-stage environment where engineers build core AI models and infrastructure from scratch. Roles include Machine Learning Scientist, Machine Learning Engineer, Infrastructure Engineer, Product Engineer (Frontend), and GTM Engineer. [jobs.ashbyhq.com/relace](https://jobs.ashbyhq.com/relace)
- **Impact**: Work on models used millions of times per week by leading AI codegen startups – direct influence on the future of software development.

## Sources
1. [relace.ai](https://relace.ai/)
2. [relace.ai/about-us](https://relace.ai/about-us)
3. [ycombinator.com/companies/relace](https://www.ycombinator.com/companies/relace)
4. [builtin.com/company/relace](https://builtin.com/company/relace)
5. [jobs.ashbyhq.com/relace](https://jobs.ashbyhq.com/relace)

## Other roles at Relace

- [Product Engineer (Frontend)](https://feeny.ai/job/product-engineer-frontend-relace-san-francisco-s47yehc0311k) — San Francisco, CA
- [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-relace-san-francisco-krnc269vmpmj) — San Francisco, CA
- [Machine Learning Scientist](https://feeny.ai/job/machine-learning-scientist-relace-san-francisco-x6cd3a3vkg65) — San Francisco, CA
- [Developer Relations Advocate](https://feeny.ai/job/developer-relations-advocate-relace-san-francisco-vxvkyvpq0gwt) — San Francisco, CA
- [Growth & Marketing Engineer](https://feeny.ai/job/growth-marketing-engineer-relace-san-francisco-pjhd6kdw85td) — San Francisco, CA
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