About the role
The candidate will have responsibilities across the following functions:
Document Intelligence:
- Build AI systems for OCR, document classification, information extraction, and document understanding.
- Develop workflows that convert unstructured real estate documents into structured, actionable data.
- Improve extraction accuracy through better data preparation, prompting, model selection, validation, and evaluation.
- Collaborate with product and operations teams to translate business and compliance requirements into ML solutions.
Backend engineering:
- Build scalable backend services and APIs using Python and frameworks such as FastAPI or Flask.
- Design REST APIs and integrations for AI, voice, and document-processing workflows.
- Implement authentication, rate limiting, retries, queuing, and failure handling.
- Debug, profile, and optimise API performance in production.
- Write clean, maintainable, well-tested code and contribute to engineering standards.
Infrastructure and MLOps:
- Containerise applications and services using Docker.
- Deploy and operate ML and backend services on Kubernetes or managed cloud platforms.
- Contribute to CI/CD pipelines, automated testing, and safe release processes.
- Implement logging, monitoring, alerting, and service-level metrics for AI systems.
- Help manage model and service deployments across development, staging, and production environments.
- Contribute to scalable, reliable, and cost-efficient cloud infrastructure.