研究工程师
Research Engineer
关于我们
Higharc 是一家由风险投资支持的初创公司，正在改变新住宅的设计和建造方式。加入一个曾为 Autodesk、Electronic Arts、Nike 和 Apple 开发过产品的创始团队。我们已获得超过 17.5 亿美元的融资，得到了顶级风险投资公司以及超过 18 家战略投资者的支持：这些投资者是建筑、建筑材料制造和分销行业的领军企业。
Higharc 正在招聘一名研究工程师加入我们的特别项目团队。在这个职位上，你将进行住宅建筑领域的空间 AI 基础研究——开发强化学习、计算机视觉、大语言模型（LLM）和 3D 几何交叉领域的创新方法，解决没有现成解决方案的问题。
你将负责的工作
你将产出推动 Higharc AI 平台的研究能力，处理其他地方不存在的问题。预期工作包括：
- 在住宅建筑的空间推理领域开展原创研究，开发能够理解建筑结构、构件之间的空间关系以及影响房屋建造的几何约束的模型。
- 设计针对建筑领域的端到端 LLM 训练和微调流程，从建筑图纸、建筑规范、产品规格和施工文档中开发领域特定的预训练和 SFT 数据集。
- 应用计算机视觉技术从建筑输入中提取语义结构，并开发多模态训练流程，将建筑数据的视觉和文本表示联系起来，使模型能够同时处理图纸、规范和法规要求。
- 开发基于强化学习的生成式建筑设计方法和架构 RAG 系统，将 LLM 输出与权威建筑知识库结合，减少高风险建筑决策中的幻觉现象。
- 定义建筑领域基准，构建真实数据集，并建立评估流程，根据实际房屋建造任务而不是通用基准来衡量模型性能。研究新兴的基础模型和参数高效微调方法（如 LoRA、QLoRA、适配器层），以指导 Higharc 的模型策略。
- 提供可集成的研究成果，包括文档化的模型制品、可部署的流程以及清晰的 API 合约，并与原型工程师合作部署微调模型和 RAG 系统
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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.