AI/ML Engineer

About Product 

We develop cutting-edge AI-powered recommendation systems for e-commerce and real estate sectors. Our solutions help clients create personalized user experiences using modern artificial intelligence technologies.

How it works?
The ETL pipeline forms the foundation of our system, efficiently processing store product data through four key stages: raw data extraction from e-commerce platforms, preprocessing for standardization, thorough validation, and structured saving into our database ecosystem. This ensures all product information, including descriptions, specifications, and images, maintains consistent quality and format for downstream processing.

Our system utilizes a sophisticated multi-database approach where the Products Database stores core product information, complemented by vector databases for semantic search capabilities. The Products Metadata maintains structured categorization of items and their attributes, while Store Metadata holds essential business information about shipping, returns, and FAQs. User Context Data captures and maintains session information for personalized shopping experiences.
 

The Context Manager serves as the central orchestrator of our platform, coordinating all agent interactions and managing session data flow. It ensures seamless communication between different AI agents and maintains user context throughout the shopping journey, enabling personalized and contextually relevant product recommendations.
 

Our system employs a network of specialized AI agents working in harmony: the Recommendation Agent generates precise product searches using LLM-powered SQL queries, the Q&A Agent provides detailed product information, while the Alternatives and Bought Together Agents suggest complementary items. The Result Enrichment Agent enhances product descriptions, and the Related Query Agent generates relevant follow-up questions to better understand customer needs.
 

The Comparison Agent provides comprehensive product analysis by examining both similarities and differences between items. It processes multiple products simultaneously and merges the results into clear, actionable insights, helping customers make informed purchasing decisions through detailed product comparisons.
 

Responsibilities

System Development and Support

• Design and develop ETL pipelines for processing data from various sources
• Create and optimize multi-component database architecture (relational and vector databases)
• Develop and integrate AI agents for various tasks: recommendations, Q&A, alternatives analysis
• Implement context management systems for coordinating AI agents' operations
   

AI/ML Development

• Develop and optimize LLM-powered systems for generating SQL queries based on natural language
• Create semantic search systems using vector databases
• Implement personalization algorithms and contextual recommendations
• Develop result enrichment systems using AI
   

Requirements

Technical Skills

• Strong proficiency in Python
• Experience with modern Large Language Models (LLMs)
• Experience in developing and optimizing ETL pipelines
• Deep understanding of recommendation systems principles
• Experience with vector and relational databases
• REST API development skills
   

Knowledge Base

• Understanding of machine learning and deep learning principles
• Knowledge of Natural Language Processing (NLP) methods
• Experience with semantic search systems
• Understanding of multi-agent system principles
   

Work Experience

• 2+ years of experience in developing production ML systems
• Experience in creating scalable recommendation systems
• Practical experience integrating AI solutions into existing business processes
   

Nice to Have

• Experience with e-commerce platforms
• Knowledge of real estate sector specifics
• Experience with microservice architecture
• ML systems performance optimization skills
   

Benefits

• Work on innovative AI projects
• Opportunity to influence architecture and technology stack
• Professional growth in AI/ML field
• Work with modern technologies and tools
  
   

Key Projects You'll Work On
 

E-commerce Recommendation System

• Develop intelligent product discovery modules using natural language processing
• Create smart Q&A widgets for product pages
• Implement sophisticated "bought together" recommendation algorithms
• Build context-aware user session management systems
   

Real Estate Recommendation System

• Create property matching systems based on natural language queries
• Develop property comparison and analysis tools
• Implement intelligent follow-up question generation
• Build systems for maintaining search context throughout the user journey
   

Technical Environment

• Multi-database ecosystem including vector databases for semantic search
• LLM-powered SQL query generation systems
• ETL pipelines for structured and unstructured data
• Context management and orchestration systems
• AI agents network architecture