עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מלאה
25,000-35,000 ₪
What We're Looking For
Role Overview: You will take ownership of the search infrastructure for Ask our company - a financial intelligence platform powered by LLMs. Your main goal is to ensure our AI agents can find the exact financial data they need (articles, transcripts, news) in milliseconds. You will work on the Retrieval layer of our RAG architecture, combining traditional text search with modern vector search techniques.
Tech Stack: Elasticsearch (v8+), Python (FastAPI, Asyncio), OpenAI Embeddings, LangChain, LangSmith.
What You'll Do
Search Engine Development: Design and implement Hybrid Search strategies. You will figure out how to best combine "keyword matching" (finding specific tickers like 'AAPL') with "semantic search" (finding concepts like 'revenue growth').
Relevance Tuning: You are responsible for the quality of search results. You will build systems to measure and improve how well the search engine answers user queries (using tools like LangSmith).
Vector Search & RAG: Manage the integration of OpenAI embeddings into Elasticsearch. You will solve challenges related to indexing long documents (e.g., earnings transcripts) so the AI retrieves only the most relevant parts.
Performance Optimization: Optimize Elasticsearch queries and index settings to ensure low latency, even for complex queries with many filters.
Python Backend: Develop and maintain the Python services that build queries and process results. We use FastAPI and Asyncio heavily.
Role Overview: You will take ownership of the search infrastructure for Ask our company - a financial intelligence platform powered by LLMs. Your main goal is to ensure our AI agents can find the exact financial data they need (articles, transcripts, news) in milliseconds. You will work on the Retrieval layer of our RAG architecture, combining traditional text search with modern vector search techniques.
Tech Stack: Elasticsearch (v8+), Python (FastAPI, Asyncio), OpenAI Embeddings, LangChain, LangSmith.
What You'll Do
Search Engine Development: Design and implement Hybrid Search strategies. You will figure out how to best combine "keyword matching" (finding specific tickers like 'AAPL') with "semantic search" (finding concepts like 'revenue growth').
Relevance Tuning: You are responsible for the quality of search results. You will build systems to measure and improve how well the search engine answers user queries (using tools like LangSmith).
Vector Search & RAG: Manage the integration of OpenAI embeddings into Elasticsearch. You will solve challenges related to indexing long documents (e.g., earnings transcripts) so the AI retrieves only the most relevant parts.
Performance Optimization: Optimize Elasticsearch queries and index settings to ensure low latency, even for complex queries with many filters.
Python Backend: Develop and maintain the Python services that build queries and process results. We use FastAPI and Asyncio heavily.
Requirements:
Elasticsearch Expert: 5+ years of experience working with Search Engines in production. You understand how indices, analyzers, and mappings work "under the hood."
Search Theory: You understand the difference between Lexical Search (keywords) and Vector Search (meaning), and know when to use which.
Python Proficiency: Strong experience with Python 3.10+. You are comfortable writing asynchronous code (async/await) and building APIs.
Data Engineering: Experience designing data schemas for search (how to structure JSON documents for efficient retrieval).
Nice to Have
Experience building RAG (Retrieval-Augmented Generation) pipelines.
Familiarity with LangChain or similar LLM frameworks.
Experience with Evaluation tools (like LangSmith) to test search quality automatically.
Background in Finance (understanding tickers, earnings calls, etc.).
Elasticsearch Expert: 5+ years of experience working with Search Engines in production. You understand how indices, analyzers, and mappings work "under the hood."
Search Theory: You understand the difference between Lexical Search (keywords) and Vector Search (meaning), and know when to use which.
Python Proficiency: Strong experience with Python 3.10+. You are comfortable writing asynchronous code (async/await) and building APIs.
Data Engineering: Experience designing data schemas for search (how to structure JSON documents for efficient retrieval).
Nice to Have
Experience building RAG (Retrieval-Augmented Generation) pipelines.
Familiarity with LangChain or similar LLM frameworks.
Experience with Evaluation tools (like LangSmith) to test search quality automatically.
Background in Finance (understanding tickers, earnings calls, etc.).
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
רמת גן
בוקר
1 חודשים
