AI Engineer (PropTech) (Clone)

Overview

Job Title: AI Engineer (PropTech)

Experience: 2–5 Years
Employment Type: Full-time

Job Overview
We are looking for a skilled AI Engineer with 2–5 years of experience to design, develop, and deploy AI-driven solutions within the PropTech (Property Technology) domain. The ideal candidate will have hands-on experience in machine learning, generative AI, and data-driven applications, preferably related to real estate platforms, property analytics, or smart property management systems.

Key Responsibilities
Design, build, and deploy AI/ML models for PropTech applications such as property valuation, demand prediction, recommendation engines, and document analysis.
Develop and integrate AI-powered features into real estate platforms and digital property solutions.
Work with large property datasets to extract insights and improve decision-making models.
Build APIs and scalable backend services to support AI models in production environments.
Implement NLP and computer vision solutions for property listings, image analysis, and document processing.
Collaborate with product, engineering, and data teams to deliver AI-driven solutions.
Optimize models for performance, scalability, and accuracy.
Stay updated with emerging AI technologies and PropTech innovations.

Required Skills
2–5 years of experience in AI/ML engineering or data science roles.
Strong proficiency in Python.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Knowledge of Generative AI, LLMs, or NLP applications.
Experience with data preprocessing, feature engineering, and model deployment.
Familiarity with REST APIs, microservices architecture, and cloud platforms (AWS, Azure, or GCP).
Strong understanding of SQL/NoSQL databases.
Experience with Docker or containerized deployments.

Good to Have
Experience in PropTech platforms or real estate data analytics.
Knowledge of computer vision for property image analysis.
Experience with LLM frameworks such as LangChain, LlamaIndex, or RAG architectures.
Experience working with geospatial data or property valuation models.
Familiarity with vector databases (Pinecone, Weaviate, FAISS).

Qualifications
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.