Junior AI Software Engineer

At Talisik Labs, we craft generative AI-powered tools including the Unified Salina App (salina. app) and the V4 media monitoring platform (media-meter. com). Were seeking a passionate individual to join our Search Team and help build next-generation search technologies.

Role Summary: Youll develop hybrid search systems integrating lexical and semantic search with Reciprocal Rank Fusion (RRF), implement knowledge graph systems using Neo4J and Graphiti, and build feature engineering pipelines for social media data. Youll gain exposure to GraphRAG and modern search evaluation methodologies.

Key Responsibilities

Hybrid Search & Semantic Systems

• Develop advanced search algorithms combining lexical and semantic methodologies
• Implement RRF techniques and vector-based semantic search using modern embedding techniques
• Design scalable search architectures for complex query processing
  
  

• Build and maintain knowledge graph systems using Neo4J and Graphiti
• Implement Graph-based RAG for enhanced search intelligence
• Design graph schemas and develop graph traversal algorithms
  
  

• Design feature engineering pipelines for social media data
• Develop topic clustering algorithms for content categorization
• Implement real-time feature generation for dynamic content
  
  

• Build advanced indexer systems using Elasticsearch
• Design and optimize search index schemas for diverse content types
• Develop comprehensive evaluation frameworks and A/B testing infrastructure
  
  

• Design scalable microservices using saga pattern for distributed search
• Develop FastAPI-based high-performance search APIs
• Implement event-driven architectures for real-time updates
  
  

• Write clean, well-documented Python code following OOP principles
• Implement comprehensive testing strategies
• Participate in code reviews and agile practices
  
  

• Programming: Proficiency in Python, ideally with some exposure to AI/ML libraries and search-related tools.
• Information Retrieval: Familiarity with search algorithms, ranking strategies, and how relevance is measured.
• Machine Learning & Semantic Search: Experience or working knowledge of vector databases, embeddings, and semantic search is a plus, but not strictly required.
• Graph Databases: Familiarity with graph database concepts (e.g., Neo4j) is beneficial.
• Search Engines: Some hands-on experience with Elasticsearch or similar platforms is preferred.
• APIs: Comfortable working with modern APIs; experience using FastAPI is an advantage.
  
  

• Backend Framework: FastAPI
• Databases: MongoDB, PostgreSQL, Neo4J, Redis
• Search Engine: Elasticsearch
• Knowledge Graph: Graphiti
• Analytics: Metabase
• Orchestration: Apache Airflow
• AI/ML Tools: Vector databases, embedding models, semantic search frameworks