Note: The job is a remote job and is open to candidates in USA. Higharc is a VC-backed startup changing how new homes are designed and built. The Applied Research Engineer will turn spatial AI research into product capabilities by training and adapting models, building supporting pipelines, and shipping reliable components for Higharc's generative floor plan engine. The role also involves optimizing latency and cost, extending research capabilities, partnering on MLOps and deployment, and mentoring team members.
Responsibilities
- Build the component layer around our layout synthesis engine: a documented API contract, a service the product can call, and an evaluation gate that runs on every change
- Turn model retraining into a one-command job, with benchmarks built in and results the whole team can read
- Own the 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, and mentor researchers and interns on engineering practices
- Share your work in writing through weekly status updates, clear pull requests, and design notes before big changes
Skills
- 5+ years of professional software development, including at least 2 years training and shipping ML models to real users
- Taken at least one model end to end: data preparation, training, evaluation, serving, and the integration that put it in front of users
- Fluency in Python and PyTorch (TensorFlow or Keras is fine if you're ready to move to PyTorch)
- Experience with geometric or structured data such as floor plans, CAD or BIM, graphs, or 2D and 3D geometry
- Built or maintained an evaluation harness or benchmark and used it to gate changes
- Packaged a model behind an API (FastAPI or similar) and owned its latency and cost
- A master's degree in computer science, machine learning, or a related field, or equivalent shipped work (a PhD is not required)
- A background in architecture or building, whether that's a degree, professional practice, or AEC software work
- Experience with constraint solvers like OR-Tools CP-SAT, optimization in general, or generative models for layouts and floor plans
- Plugin or tooling work in Rhino, Grasshopper, or Revit, or experience with Hugging Face, experiment tracking, and cloud model serving on AWS or Modal, plus any publications or open source contributions
Benefits
- Significant equity
- Comprehensive medical coverage for all U.S.-based full-time employees
- Comprehensive dental coverage for all U.S.-based full-time employees
- Comprehensive vision coverage for all U.S.-based full-time employees
- Flexible PTO for all U.S.-based full-time employees
- Meaningful maternity/paternity leave for all U.S.-based full-time employees
- Short- and long-term disability plans
- 401(k)
- A stipend to create the ideal home office
- Support ongoing learning and development (L&D)
- Entirely remote work
- Flexibility to blend work and life
Company Overview