AI Engineer: Computer Vision, LLMs & ML
About the position Intellus Build is seeking a founding AI Engineer to join their team and transform the global construction industry. The company aims to create an AI-native operating system that connects project data from initial planning to final completion, addressing the current inefficiencies in the industry that rely on outdated methods like spreadsheets and WhatsApp. The role involves building AI systems that can process and interpret vast amounts of unstructured data from construction sites, such as photos, documents, and sensor readings, to provide actionable intelligence. The goal is to make construction sites safer and more efficient by developing cutting-edge AI applications that can be deployed even in challenging environments with limited connectivity.
Responsibilities
- Build RAG systems that understand construction terminology.
- Deploy computer vision models to detect safety violations from site photos.
- Create AI assistants that can answer project status queries by reasoning across various project documents.
- Design real-time progress tracking systems that function in low-connectivity environments.
- Build domain-aware AI to enhance construction site safety and efficiency.
- Develop verification systems to track equipment throughout complex supply chains.
Requirements
- Recent graduate from a top AI program (Stanford AI Lab, MIT CSAIL, or equivalent) OR 2-3+ years of experience building production ML systems.
- Focus on practical AI applications.
- Comfortable with the full ML stack: data processing, model selection, deployment, and monitoring.
- Ability to move quickly and prototype rapidly.
- Shipped at least one LLM-based application used by real users.
- Experience with RAG, embeddings, and vector databases.
- Strong Python skills with PyTorch, TensorFlow, or JAX.
- Ability to explain complex ML concepts to non-technical stakeholders.
Nice-to-haves
- Computer vision experience (YOLO, Segment Anything, etc.).
- Published ML research or Kaggle competition medals.
- Experience with construction, manufacturing, or industrial datasets.
- Track record of optimizing inference costs.
Benefits
- Founding-team equity (1-2%)
- Base salary
- Remote-friendly work environment
- Async-first communication
- Zero bureaucracy
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