The ad says“Experience with 3D modeling, computational geometry, or computer graphics in a research or production context”
The ad says“Experience with 3D modeling, computational geometry, or computer graphics in a research or production context”
The ad says“Experience with 3D modeling, computational geometry, or computer graphics in a research or production context”
The ad says“Hands-on experience with model training frameworks (HuggingFace Transformers, PyTorch) and fine-tuning workflows on domain-specific corpora”
The ad says“Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and embedding model selection”
The ad says“Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and embedding model selection”
The ad says“Strong proficiency in Python across the ML ecosystem; React/TypeScript proficiency for integration work”
The ad says“Hands-on experience with model training frameworks (HuggingFace Transformers, PyTorch) and fine-tuning workflows on domain-specific corpora”
The ad says“Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and embedding model selection”
The ad says“Strong proficiency in Python across the ML ecosystem; React/TypeScript proficiency for integration work”
The ad says“Strong proficiency in Python across the ML ecosystem; React/TypeScript proficiency for integration work”
The ad says“Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and embedding model selection”
The ad says“Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and embedding model selection”
Values
The ad says“Familiarity with BIM tools (Revit, AutoCAD) or BIM data formats (IFC, gbXML)”
The ad says“Familiarity with BIM tools (Revit, AutoCAD) or BIM data formats (IFC, gbXML)”
The ad says“Familiarity with BIM tools (Revit, AutoCAD) or BIM data formats (IFC, gbXML)”
The ad says“Experience with Three.js or equivalent 3D frameworks”
Higharc is hiring a Research Engineer to join our Special Projects team. In this role, you’ll conduct foundational research in spatial AI for residential construction — developing novel approaches at the intersection of reinforcement learning, computer vision, LLMs, and 3D geometry to solve problems that have no off-the-shelf solutions
You’ll produce the research capabilities that power Higharc’s AI platform, working on problems that don’t exist anywhere else
Design and conduct original research in spatial reasoning for residential construction, developing models that understand architectural structure, spatial relationships between building components, and the geometric constraints that govern how homes can be built
Design end-to-end LLM training and fine-tuning pipelines tailored to construction domains, developing domain-specific pre-training and SFT datasets from architectural drawings, building codes, product specifications, and construction documentation
Apply computer vision techniques to extract semantic structure from architectural inputs and develop multimodal training pipelines that link visual and textual representations of building data, enabling models that reason across drawings, specifications, and code requirements simultaneously
Develop RL-based approaches for generative architectural design and architect RAG systems that ground LLM outputs in authoritative construction knowledge bases, reducing hallucination for high-stakes building decisions
Define construction-domain benchmarks, build ground-truth datasets, and establish eval pipelines that measure model performance against real homebuilding tasks rather than generic benchmarks. Research emerging foundation models and parameter-efficient fine-tuning approaches (LoRA, QLoRA, adapter layers) to inform Higharc’s model strategy
Deliver research outputs ready for integration, including documented model artifacts, serving-ready pipelines, and clear API contracts, and partner with the Prototyping Engineer to deploy fine-tuned models and RAG systems into the Higharc platform
Benefits
Medical/Dental/Vision Benefits Package
Remote-First
Unlimited Vacation
Offices in Raleigh/Durham, San Francisco, and Atlanta open 24/7 to Employees
Employee Care Packages (Snacks/Drinks/Gifts) Sent Directly to You!
Preferred experience
You do your best work when you can go deep. You treat residential construction as a worthy and complex problem space, not a stepping stone to a more prestigious domain, and you bring the same intellectual honesty to negative results as to positive ones
You understand that research that never ships is indistinguishable from research that never happened
5+ years of professional software engineering experience, with 2+ years directly on LLM development, fine-tuning, or applied ML systems in production
Strong proficiency in Python across the ML ecosystem; React/TypeScript proficiency for integration work
Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and embedding model selection
Experience with 3D modeling, computational geometry, or computer graphics in a research or production context
Hands-on experience with model training frameworks (HuggingFace Transformers, PyTorch) and fine-tuning workflows on domain-specific corpora
A Master’s degree in Computer Science, Machine Learning, AI, or a closely related field
While we’ve identified the core experience and skills required above, please still apply if you have more or different experience than this!
A Ph.D., particularly for candidates focused on model research and pre-training
Open-source contributions or published research
Experience with Three.js or equivalent 3D frameworks
Familiarity with BIM tools (Revit, AutoCAD) or BIM data formats (IFC, gbXML)
Recruitment process
We will use your previous experience and performance across the series of interviews to establish appropriate level within our organization in a fair and equitable way
