Applied Research Engineer

Remote (New York City, NY) · Remote (San Francisco, CA) · 5+ years experience · Full-time · Remote · Posted Sep 29, 2026

At a glance

Higharc is a VC-backed startup that is changing how new homes are designed and built. Join a founding team who’ve shipped products for Autodesk, Electronic Arts, Nike, and Apple. We have raised over $175M with support from top-notch venture capital firms and more than 18 strategic investors: industry leaders in construction, building products manufacturing, and distribution.
Higharc is seeking a hands-on Applied Research Engineer to turn our spatial AI research into capabilities that homebuyers and builders use. You'll join our Platform R&D team, taking models that have proven themselves in research and shipping them into the product.

Higharc is seeking an Applied Research Engineer to join the Platform R&D team and transition spatial AI research into functional product capabilities.
The role focuses on training, adapting, and deploying models into a production environment while managing latency and cost budgets.

Build component layers around the layout synthesis engine including API contracts and evaluation gates.
Automate model retraining processes with integrated benchmarks.
Manage latency and cost budgets for learned capabilities.
Extend core research into new capabilities such as multi-story plans and real-time editing.
Partner with infrastructure engineers on MLOps and deployment.
Mentor researchers and interns on engineering practices.
Document work through weekly status updates, pull requests, and design notes.

5+ years of professional software development experience.
At least 2 years of experience training and shipping ML models to real users.
End-to-end experience taking a model from data preparation to integration.
Fluency in Python and PyTorch.
Experience with geometric or structured data such as floor plans, CAD, BIM, graphs, or 2D/3D geometry.
Experience building or maintaining an evaluation harness or benchmark.
Experience packaging models behind an API such as FastAPI.
Master's degree in computer science, machine learning, or related field, or equivalent shipped work.
Comfort working remotely on US Eastern hours.

Background in architecture or building (degree, professional practice, or AEC software work).
Experience with constraint solvers like OR-Tools CP-SAT.
Experience with optimization or generative models for layouts and floor plans.
Plugin or tooling work in Rhino, Grasshopper, or Revit.
Experience with Hugging Face, experiment tracking, and cloud model serving on AWS or Modal.
Publications or open source contributions.