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.
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.
This role is going to be sitting on our AI and ML team as a backend engineer.
You will be working directly with our in house models (as well as frontier VLMs) so that we can build a world class interaction for the frontend. For example, you could be taking a segmentation mask that one of our detection models produces, deciding what it should become on the canvas - a polygon, a polyline, a set of connection ports - designing the contract that carries it there, and then making it something an estimator can grab and correct.
The job is not just "make the model better", it’s to have the ideal shape and use case for the user can see, trust, correct, and bill against.
Design the perception → product data contract
Ship AI geometry into the canvas
Own the accuracy and UX tradeoff honestly
Close the correction loop
Be the translation layer between our AI/ML team and the product engineers
We're looking for someone comfortable working largely across the stack. You should be comfortable reading a PyTorch postprocessing path and then understanding the flow to the canvas rendering path in the afternoon. You should be willing to dive deeper into understand model architectures and spotting inefficiencies as their outputs are translated downstream.
6+ years of industry software engineering experience
If fewer than 6 years of experience, still encouraged to apply!
Shipped computer vision or ML output into a product surface that users interact with and correct - not just into a report, a metric, or an eval
Comfortable in Python and TypeScript
Experience designing and versioning data contracts between services on live customer data
Canvas and rendering experience
Experience building human in the loop labeling or active learning loops
Construction, CAD, GIS, or another domain where drawings are the source of truth
Salary: Competitive base salary
Equity: Meaningful equity package, commensurate with experience
Benefits: Comprehensive medical, dental, and vision coverage
Perks:
Agentic tooling budget
Lunches provided, dinners provided (after a set time)
Great culture and office banter
This is a salaried, onsite role located in New York City's Flatiron district. We are still a startup! We love working onsite together and believe strongly that this gives us for creative problem-solving, and building strong connections. You'll be at the heart of our fast-paced operations, actively contributing to a culture that values engagement, growth, and teamwork.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Rebar is building the next-generation operating system for commercial HVAC, electrical, and plumbing suppliers and subcontractors. Their V1 quoting product has scaled significantly, doubling revenue and gaining adoption across top suppliers.