Software Engineer
US$200,000 – US$260,000 / yr base salary
Posted 28 May 2026
Advertised as “Software Engineer, ML Infrastructure”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
| Base salary | US$200,000 – US$260,000 / yr |
|---|
Senior ML Infrastructure Engineer
About Rebar
Rebar is building the AI operating system for commercial HVAC, Electrical, and Plumbing.
Over the past year our quoting platform has processed tens of thousands of projects across North America and we’re continuing that growth. Our customers include many of the top firms in the industry. Some of these companies are running billion dollar construction projects on workflows that still look like it's 1985.
Construction is 10% of GDP and still massively underserved by software. We are changing that.
We recently raised a $14M Series A from leading construction tech investors and are entering our next phase of growth. We are building a set of AI native products that will define how this industry operates.
About the Engineering Org
The role of the engineer is rapidly changing. We're aware and we're being very intentional of ensuring we adapt with it. We are fostering an engineering culture of growth and development. We strongly emphasize care of craft and winning together. To echo our values, everyone operates like an owner, we find a way, and we win together.
About the Role
We're hiring a Software Engineer to own and expand the ML infrastructure platform our ML engineers depend on to rapidly iterate, experiment, and ship models. This work will span feature pipelines, training infra, evaluation, deployment, and monitoring. You should be well versed with GPU architecture and performance focused - understanding what is blocking the engineers as well as our MFU. You'll be joining a small group of talented engineers focused on delivering practical, production-ready ML systems in a fast-moving startup context.
The role is ideal for someone who is obsessive over the developer experience of the engineers they support, is interested in training, and meticulous over performance. Our team is still (somewhat) lean and engineers wear many hats. Your purview will span the whole ML lifecycle.
Responsibilities
-
Platform and Developer Experience
- You'll help build services that act as the single front door to our ML platform
-
Model and Data Governance
- Explore and help instrument our active learning pipelines, retrainings, model registry, and more
-
Infrastructure Consolidation and Integration
- Smooth the seams for GPU inference and our cloud stack