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 team 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 part of this group, you will help establish a new research area within the company, building AI workflows that digests a large amount of construction documents and models to help with one of the product core processes.

What You’ll Do:

• Take part in all development aspects—from design to production—of LLM-based workflows to digest information from a variety 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

What We’re Looking For:

• B.Sc. in Electrical Engineering, Computer Science or equivalent (Msc advantage)
• 4+ 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
• 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

Preferred Qualifications:

• Expertise in Retrieval-Augmented Generation, vector databases, embedding model selection, and retrieval optimization
• Experience designing and implementing agentic LLM workflows incorporating tool use and memory components
• Deep understanding of LLM application patterns, tool use, function calling
• Develop complex multi-step agentic workflows with observability, guardrails, and cost controls
• Familiarity with LangGraph or other LLM frameworks

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