Description:.Responsibilities
Implement document preprocessing pipelines for contextual embeddings and BM25
Build and improve UI components for our RAG system dashboard
Develop integration points between different components of the retrieval system
Test and compare different retrieval strategies across various knowledge domains
Help implement evaluation frameworks to measure retrieval performance
Contribute to documentation and technical resources for both internal and external use
Requirements
Experience with frontend and backend development
Understanding of embedding models and vector search concepts
Familiarity with REST APIs and data processing pipelines
Knowledge of modern web development frameworks
Ability to work with Python for data processing tasks
Experience with databases (SQL and/or vector databases)
Solid testing and debugging skills
Good communication and collaboration abilities
Nice to Have
Experience with BM25, TF-IDF, or other lexical search algorithms
Knowledge of LLMs and prompt engineering
Familiarity with performance optimization techniques
Understanding of evaluation metrics for information retrieval
Experience with data visualization or dashboard development
Background or interest in NLP or computational linguistics
Previous work with document processing or chunking strategies
Salary: TBD
Apply: THINK YOU ARE A GOOD FIT? SUBMIT YOUR RESUME FOR THE POSITION TODAY! CONTACT@POLYSENTRY.COM
Job type: Full‑time
Work mode: remote
To apply for this job email your details to CONTACT@POLYSENTRY.COM
