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Spacial AI

AI-powered pre-construction documents with engineer review

AI Researcher

Full-TimeUpdated on 10/15/2026
No salary listed
Senior
PhD
Tel Aviv-Yafo, Israel
Hybrid
AI & Machine LearningAI Research

About the job

Requirements
  • A Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related quantitative field such as Mathematics, Physics, Electrical Engineering, or Computational Biology.
  • At least 5 years of combined experience in AI/ML research and development, focused on Generative AI, LLMs, and Deep Learning.
  • A strong research-impact track record, including publications in top-tier conferences or significant open-source contributions or patents in AI/ML.
  • Expertise in the theory and practical application of LLM fine-tuning, advanced RAG architectures, and complex agentic systems.
  • Proficiency in Python and expertise with major machine learning and deep learning frameworks, including PyTorch, TensorFlow, and Hugging Face Transformers.
  • A strong foundation in software engineering and algorithm development, with experience working with large datasets.
Responsibilities
  • Conduct research, design, and implement novel Generative AI systems using LLMs, vision-language models, and advanced agentic frameworks such as LangChain and LlamaIndex.
  • Develop and optimize algorithms and methodologies for LLM fine-tuning, retrieval-augmented generation optimization, and context engineering.
  • Conduct rigorous experimentation and evaluation of novel GenAI-powered solutions to improve model efficiency, performance, and robustness.
  • Collaborate with engineering teams to guide the translation of research prototypes into production-grade AI products.
  • Contribute to the company's long-term AI research direction and stay current with emerging techniques and academic breakthroughs.
  • Develop and implement computer vision algorithms to enhance product performance and functionality.
Desired Qualifications
  • Experience with multimodal AI, including vision-language models and diffusion models.
  • Familiarity with challenges and real-time considerations involved in managing AI workloads in a production environment.
  • Knowledge of parallel computing and optimization techniques for large-scale model training and inference.

About the company

Spacial creates AI-powered tools for pre-construction and engineering automation that convert building drawings into coordinated, code-aware construction documents. For residential projects, the platform generates structural, MEP, and energy plans, with licensed engineers reviewing each set to ensure they’re ready for construction in days rather than through long manual coordination. The core AI platform lives at spacial.io, while Spacial Services handles hands-on engineering, permitting, and delivery. Unlike some builders’ workflows, Spacial combines an intelligent building model with permit logic and conflict resolution to produce ready-to-submit documentation. The company targets B2B sales to residential project teams, offering both AI document generation and engineering services to speed up pre-construction work.

Company Size

11-50

Company Stage

Seed

Total Funding

$10M

Headquarters

Palo Alto, California

Founded

2024

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Simplify's Take

What believers are saying

  • Spacial closed a $10M seed round on September 22, 2026.
  • Spacial reported 228 active U.S. projects and a first live demo at IBS 2026.
  • Ravid Shwartz-Ziv joined August 25, 2026, strengthening evaluation rigor and technical credibility.

What critics are saying

  • Higharc and FormX are funding similar residential AI workflows in 2026.
  • Stamped plan liability makes a single code failure a shutdown-level existential risk.
  • Beta opening in Q4 2026 delays proof; slow adoption lets PermitFlow own workflows.

What makes Spacial AI unique

  • Licensed engineers stamp every set, combining AI speed with professional accountability.
  • Spacial’s September 2026 beta targets 2D drawings-to-stamped structural and MEP outputs.
  • Its building model coordinates code, force distribution, and routing in one workflow.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

12%

1 year growth

12%

2 year growth

16%
GlobeNewswire
Aug 25th, 2026
Spacial names Ravid Shwartz-Ziv, PhD, as scientific advisor.

Spacial names Ravid Shwartz-Ziv, PhD, as scientific advisor. Shwartz-Ziv will advise research and engineering teams and help set Spacial's research roadmap. August 25, 2026 11:01 ET | Source: Spacial AI Inc PALO ALTO, Calif., Aug. 25, 2026 (GLOBE NEWSWIRE) - Spacial, the AI-powered engineering platform for residential construction, today announced that Ravid Shwartz-Ziv, PhD, has joined the company as a scientific advisor. An Assistant Professor and Faculty Fellow at NYU's Center for Data Science, Shwartz-Ziv leads cutting-edge Large Language Model (LLM) research focused on using information theory to explain what neural networks actually learn. He will work closely with the company's research and engineering teams, advise on major technology decisions for the platform, and assist the founders in establishing its research roadmap. Shwartz-Ziv has spent several years benchmarking and evaluating AI systems, which is relevant to a problem the construction industry hasn't solved: there is no shared standard for measuring whether an AI-generated plan is accurate, code-compliant, and internally coordinated. Further, he will guide the evolution of Spacial's core technology, a model trained to understand buildings as systems of physical relationships, which will produce permit-ready engineering documents for construction projects, an issue that is closely aligned with Shwartz-Ziv's research. "Before an engineer will stamp what our model produces, we need real confidence in what it's learned, not just how well it performs. The construction industry doesn't have a shared standard for proving that an AI-generated plan is accurate and code-compliant, and closing that gap is exactly why we brought Ravid on. He brings deep expertise in evaluating AI systems, and that's exactly the rigor Spacial needs to get structural AI right," said Maor Greenberg, co-founder and CEO of Spacial. "Permitting is a hard, practical problem, and Spacial is taking a serious technical approach to it. Confirming that a model has genuinely learned how buildings work as physical systems, not just that it can produce a plan that looks right, is exactly the kind of question my work on information theory and model evaluation was built to answer. I look forward to supporting the team as an advisor," said Ravid Shwartz-Ziv, scientific advisor to Spacial. About Spacial: Spacial is an AI-powered engineering platform that delivers fast and accurate structural plans for residential construction. The platform converts 2D architectural drawings into 3D, code-compliant construction documents with built-in design conflict detection, architectural detailing, and local code validation. Every plan undergoes a thorough evaluation and professional approval by licensed engineers before being stamped. Architects, builders, and developers rely on Spacial to reduce delays, lower costs, and streamline the construction process. With over 228+ active projects across the U.S., Spacial is redefining how residential projects get built. Visit https://spacial.io for more information.

Tech Funding News
Oct 28th, 2025
Spacial scoops $10M to disrupt residential construction with engineering automation — TFN

Spacial, founded in 2024, secured $10M seed funding to accelerate its AI-driven platform automating residential engineering and permitting, speeding up homebuilding and reducing costs across the US.