Job Description

About Buildots

Buildots is transforming construction management with AI and computer vision.

Our AI-powered SaaS platform automates on-site progress tracking, giving construction teams the tools to plan smarter, improve efficiency, and cut costly delays by up to 50%. The $13 trillion construction industry has seen little disruption in the past 150 years. Until now. Backed by leading VCs and industry pioneers, Buildots enables a new, performance-driven approach.

Deployed on hundreds of projects across North America, Europe and the Middle East, Buildots is already reshaping the future of the world's largest industry, and we're on track for rapid expansion in 2026.

Buildots’ customers include top global contractors, consultants and owners – Intel, Tidhar, Azrieli Group, VINCI Construction, Turner and Multiplex, to name a few.

About the Role

Our algorithms group is responsible for all of the AI and algorithmic challenges the company is facing, tackling complex real-world problems that directly affect the company’s success. As a lead data-scientist, you will lead a new research area and a small team within the company. This is a primarily hands-on role where you will build the AI workflows that digest a large amount of construction documents and architectural models to help with one of the product core processes.

What You’ll Do:

• Lead and mentor a small team while remaining deeply hands-on in all development aspects—from design to production—of LLM-based workflows to digest information from a variety of construction-oriented documents
• Research, design, and integrate LLMs to deliver advanced automation and reasoning capabilities
• Develop datasets and benchmarks to evaluate and monitor LLM-based applications effectively
• Build LLM evaluation and optimization processes

Requirements

Requirements:

• B.Sc. in Electrical Engineering, Computer Science or equivalent (Msc advantage)
• 5+ years of professional experience in Data Science or Applied Machine Learning
• 2+ years of experience developing production-grade software systems and working on AI & LLMs - hands on
• Proven experience managing or mentoring small technical teams
• Generative AI & LLM Expertise: Proven experience working with LLM APIs (OpenAI, Anthropic, etc.), prompt engineering and building functional AI-driven pipelines
• Startup Mindset: Ability to prioritize effectively in a dynamic environment, balancing "quick wins" for delivery with robust development for the long term
• A strong focus on data quality and optimization for LLM workflows

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