AI/ML Engineer

AI / ML Development

• Design, build, and deploy machine learning models for real estate use cases - lead scoring, demand forecasting, churn detection and organic growth
• Develop and fine-tune Large Language Models (LLMs) for property FAQ, document processing and customer communication
• Build AI agents that automate CRM workflows, follow-ups and post-sales processes end-to-end
• Implement Retrieval-Augmented Generation (RAG) pipelines over property listings, legal documents, and market reports

Data & Modelling

• Work with structured and unstructured real estate data — transaction records, listing databases, CRM and market feeds
• Build and maintain feature engineering pipelines: conduct exploratory data analysis and model evaluation
• Collaborate with data engineers to ensure clean, reliable data flows into model training and inference

MLOps & Automation

• Manage the full ML lifecycle: experimentation, versioning, deployment, monitoring, and retraining
• Build and maintain automation pipelines using workflow tools such as n8n, Zapier or custom orchestration frameworks
• Ensure models are deployed reliably with observability, alerting, and rollback mechanisms in place

Collaboration & Innovation

• Partner with product managers, operations and CRM teams to translate business problems into AI solutions
• Stay up to date on AI/ML research and evaluate emerging tools, models and frameworks relevant to Property Tech
• Document architectures, experiments and deployment processes clearly for cross-functional teams

Required Skills

Machine Learning

• 5+ years of hands-on experience building and shipping ML models in production
• Strong foundations in supervised, unsupervised and reinforcement learning
• Experience working with LLMs - prompt engineering, fine-tuning and API integration (OpenAI, Anthropic etc.)
• Familiarity with AI agent frameworks such as LangChain, LlamaIndex, CrewAI or AutoGen

MLOps & Cloud

• Experience with cloud platforms: AWS (SageMaker, Lambda, S3), GCP (Vertex AI) or Azure ML
• Proficiency in MLOps tools: MLflow, Weights & Biases or similar for experiment tracking and model versioning
• Comfort with containerisation (Docker, Kubernetes) and CI/CD pipelines for ML workloads
• Workflow automation experience with tools such as n8n, Apache Airflow etc.

Data & Engineering

• Strong SQL skills: experience with data warehouses (BigQuery, Snowflake or Redshift)
• Familiarity with data pipeline tools (dbt, Spark or Pandas at scale)
• Ability to work with APIs and integrate ML outputs into CRM

Machine Learning

• 3+ years of hands-on experience building and shipping ML models in production
• Strong foundations in supervised, unsupervised, and reinforcement learning
• Experience working with LLMs — prompt engineering, fine-tuning, and API integration (OpenAI, Anthropic, Mistral, etc.)
• Familiarity with AI agent frameworks such as LangChain, LlamaIndex, CrewAI, or AutoGen

MLOps & Cloud

• Experience with cloud platforms: AWS (SageMaker, Lambda, S3), GCP (Vertex AI), or Azure ML
• Proficiency in MLOps tools: MLflow, DVC, Weights & Biases, or similar for experiment tracking and model versioning
• Comfort with containerisation (Docker, Kubernetes) and CI/CD pipelines for ML workloads
• Workflow automation experience with tools such as n8n, Apache Airflow, or Prefect

Data & Engineering

• Strong SQL skills; experience with data warehouses (BigQuery, Snowflake, or Redshift)
• Familiarity with data pipeline tools (dbt, Spark, or Pandas at scale)
• Ability to work with APIs and integrate ML outputs into CRM, ERP, or product systems

Generative & Voice AI

• Experience with text-to-speech / speech-to-text models (ElevenLabs, Whisper etc.)
• Building voice AI agents or voice-enabled CRM integrations
• Multimodal model experience (vision + text for property image analysis)

RAG & Vector Databases

• Hands-on with vector databases and Building production RAG pipelines_

Pay: AED1.00 - AED2.00 per month

Work Location: In person