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Mid-senior ML role in metro with common GenAI skills but non-Tier1 construction focus.
Core ML/GenAI skills are transferable, but construction domain preference raises specificity.
Explicit years plus specific ML/GenAI, cloud, MLOps, and LLM experience increases filter rigidity.
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Lead design and deployment of AI/GenAI features impacting construction projects across planning, cost, risk, quality, and safety workflows.
Build, validate, and productionize machine learning models and RAG systems for scheduling, cost forecasting, risk prediction, and document intelligence in construction.
Own end-to-end AI system lifecycle including rapid prototyping, deployment, monitoring, drift detection, and ensuring enterprise-grade scalability within SaaS environments.
5–8+ years of production software development experience.
2+ years of experience building AI/ML systems.
1+ year delivering GenAI or LLM-based features.
Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or equivalent experience.
Experienced in SaaS-scale AI integrations with strong skills in PyTorch, TensorFlow, Transformers, LangChain, and MLOps practices.
Familiarity with cloud platforms (AWS, Azure, or GCP) and handling large-scale data with SQL and vector databases like FAISS or Pinecone.
Preferably has domain experience in construction or infrastructure and familiarity with construction-specific documents and workflows (BIM, BOQs, RFIs).