Job Description

We are looking for a Senior AI/ML Engineer to spearhead the design, development, and deployment of cutting-edge machine learning models that power our Search and document intelligence features. You will work closely with our Data Engineering, Product, and DevOps teams to build robust pipelines and predictive models that enable real-time property data retrieval, NLP-based document parsing, and intelligent insights for our end-users.

This is a high-impact role where you’ll directly shape the AI backbone of Landeed’s platform, tackling diverse challenges—from large-scale data ingestion and deep learning NLP to semantic search and intelligent recommendations.

Key Responsibilities

1. Model Development & Deployment
2. Design and implement ML/DL models (e.g., NLP for document parsing, text classification, semantic search) using PyTorch, TensorFlow, or Hugging Face frameworks.
3. Collaborate with DevOps to deploy and maintain these models in production, ensuring scalability and low latency.
4. NLP & Document Intelligence
5. Build and refine NLP pipelines for document analysis, OCR, and entity extraction from legal/real estate records.
6. Develop text pre-processing and feature engineering strategies to handle unstructured and multilingual data.
7. Data Pipeline & Integration
8. Work hand-in-hand with Data Engineering to design data pipelines that efficiently ingest and process large volumes of property data
9. Ensure real-time or near-real-time data flows into ML models and search indices.
10. Search Enhancement
11. Integrate ML models with Elasticsearch/OpenSearch to power advanced features like semantic search, auto-complete, and relevance ranking
12. Continuously tune models for accuracy, performance, and relevance based on user feedback and A/B testing.
13. Research & Innovation
14. Stay on top of emerging AI/ML trends, especially in NLP and information retrieval, proposing cutting-edge solutions for Landeed’s platform.
15. Experiment with LLMs (Large Language Models) for summarizing documents, extracting insights, and enhancing user queries.
16. Performance Monitoring & Optimization
17. Implement robust monitoring, alerting, and logging to track model performance in production.
18. Optimize inference pipelines for latency, throughput, and cost in a cloud environment.
19. Collaboration & Mentorship
20. Work closely with cross-functional teams (Product, Frontend, QA) to align AI/ML solutions with business goals.
21. Mentor junior engineers in best practices for model design, coding, and MLOps.

Qualifications

• 3+ years of experience in AI/ML engineering, with a focus on NLP or search
• Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with information retrieval technologies like Elasticsearch, Solr, or OpenSearch
• Practical knowledge of cloud services (AWS, GCP, or Azure) for deploying and scaling ML models.
• Familiarity with CI/CD and containerization (Docker, Kubernetes) for MLOps.
• Strong problem-solving skills and an ability to navigate complex, unstructured data environments.
• Excellent communication skills to collaborate across teams and present technical concepts effectively.

Preferred

• Experience with OCR libraries (Tesseract, AWS Textract) or advanced document processing
• Background in real estate, legal tech, or government data systems.
• Exposure to streaming technologies (Kafka, Spark Streaming) for real-time data ingestion.
• Hands-on experience with vector databases (Pinecone, Weaviate) for semantic search.

Why Join Landeed?

• High-Impact Role Shape the AI backbone of a cutting-edge real estate platform that transforms how millions access property information.
• Fast-Growing Startup Join a dynamic, collaborative environment in Hyderabad, where your ideas and expertise will be valued.
• Competitive Compensation Receive a fixed salary plus equity, aligning your success with the company’s growth.
• Professional Growth Work with talented peers and stay at the frontier of AI/ML innovations in NLP and information retrieval.