Description review
Research Engineer
Higharc · United States · back to the listing
HR standards
57/100
needs work
Title ↔ description
66/100
needs work
Reads as
Machine Learning Engineer
99% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
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What the listing never says
- 16 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
About Us
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 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.
What You'll Do
You'll produce the research capabilities that power Higharc's AI platform, working on problems that don't exist anywhere else. Expect to:
• 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.
About You
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.
You have:
• 5+ years of professional software engineering experience, with 2+ years directly on LLM development, fine-tuning, or applied ML systems in production
• Hands-on experience with model training frameworks (HuggingFace Transformers, PyTorch) and fine-tuning workflows on domain-specific corpora
• 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
• Strong proficiency in Python across the ML ecosystem; React/TypeScript proficiency for integration work
• A Master's degree in Computer Science, Machine Learning, AI, or a closely related field
A major plus if you also bring:
• A Ph.D., particularly for candidates focused on model research and pre-training
• Open-source contributions or published research
• Familiarity with BIM tools (Revit, AutoCAD) or BIM data formats (IFC, gbXML)
• Experience with Three.js or equivalent 3D frameworks
While we've identified the core experience and skills required above, please still apply if you have more or different experience than this! 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.
Working at Higharc
Remote work and travel: Our company is entirely remote, and has been since we were founded in 2018. Remote work means more time with family, less time commuting, and the flexibility to blend work and life. We value in-person collaboration and asynchronous deep-work time, which is why we schedule regular team meet-ups in our hubs across the US and, depending on the role, prioritize hiring in those hubs. If your role requires frequent travel beyond pre-scheduled team meet ups, we will represent that to the best of our ability as early as possible in the interview process.
Compensation and benefits: Higharc offers competitive salaries with significant equity, in a fast-growing, well-funded company. We provide comprehensive medical, dental, and vision coverage, with flexible PTO, and meaningful maternity/paternity leave to all U.S based employees that are full-time. You'll also have access to other big-company benefits such like short and long-term disability plans and a 401K. We also provide a stipend to create the ideal home office and support ongoing L&D.
Please note: we are seeing an uptick of fraudulent recruiting activity claiming to be associated with Higharc. All communication and outreach from our in-house team will come from an @higharc.com email address.
Originally posted on Himalayas
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 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.
What You'll Do
You'll produce the research capabilities that power Higharc's AI platform, working on problems that don't exist anywhere else. Expect to:
• 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.
About You
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.
You have:
• 5+ years of professional software engineering experience, with 2+ years directly on LLM development, fine-tuning, or applied ML systems in production
• Hands-on experience with model training frameworks (HuggingFace Transformers, PyTorch) and fine-tuning workflows on domain-specific corpora
• 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
• Strong proficiency in Python across the ML ecosystem; React/TypeScript proficiency for integration work
• A Master's degree in Computer Science, Machine Learning, AI, or a closely related field
A major plus if you also bring:
• A Ph.D., particularly for candidates focused on model research and pre-training
• Open-source contributions or published research
• Familiarity with BIM tools (Revit, AutoCAD) or BIM data formats (IFC, gbXML)
• Experience with Three.js or equivalent 3D frameworks
While we've identified the core experience and skills required above, please still apply if you have more or different experience than this! 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.
Working at Higharc
Remote work and travel: Our company is entirely remote, and has been since we were founded in 2018. Remote work means more time with family, less time commuting, and the flexibility to blend work and life. We value in-person collaboration and asynchronous deep-work time, which is why we schedule regular team meet-ups in our hubs across the US and, depending on the role, prioritize hiring in those hubs. If your role requires frequent travel beyond pre-scheduled team meet ups, we will represent that to the best of our ability as early as possible in the interview process.
Compensation and benefits: Higharc offers competitive salaries with significant equity, in a fast-growing, well-funded company. We provide comprehensive medical, dental, and vision coverage, with flexible PTO, and meaningful maternity/paternity leave to all U.S based employees that are full-time. You'll also have access to other big-company benefits such like short and long-term disability plans and a 401K. We also provide a stipend to create the ideal home office and support ongoing L&D.
Please note: we are seeing an uptick of fraudulent recruiting activity claiming to be associated with Higharc. All communication and outreach from our in-house team will come from an @higharc.com email address.
Originally posted on Himalayas