Text Search Engines

Nikunjkumar

Android

Developers with experience creating internet search engines and mapping tools to code search algorithms or enhance experiences in Google, Yahoo!, Bing etc. Find Text Search Engines WFH freelancers on November 17, 2024 who work remotely. Read less

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Software developers skilled in Java, ETL and API calls as

Full Stack Developers

Hire front-end developers for web apps and website templates (HTML,

Frontend Development

Build fast, stable back-end solutions with client-side technologies like JavaScript

Backend Development

PHP developers (composer, PHPUnit, Laravel) for object-oriented programming (Python, Java,

PHP Framework

Develop reliable web application front-ends using HTML, Cascading style sheets

HTML / CSS

Develop systems with coders in PHP, Java, Python, C#; experienced

Content Management System (CMS)

Build visually compelling, interactive user experiences across mobile, tablet and

UX / UI / Responsive

ECommerce

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Wikipedia Text Search Engines Courses

Top Frequently Asked Questions

Building search engines

What kind of developer codes search engines?

If you want to build a text search engine capable of handling hundreds of millions of users, transactions, and scaling queries in real-time, start with a Machine Learning and Artificial Intelligence (AI) developer who loves writing API code to create smarter ranking algorithms that balances user attention and surfaces more relevant content in random search queries. The right hire will have a mastery of Java, Python, JavaScript or Rust with experience in Open Source and SaaS products such as Postgres, Redis, AWS Kinesis, DynamoDB. Proficiency in NoSQL database/services such as Solr, Elasticsearch, Dynamo, Athena, Data-Lake should be non-negotiable.

Coding search engines with AI services to account for user behavioral tracking, recommendations, personalization, candidate matching, and ontology, takes much more than amalgamating open-source libraries and AWS services together or developing a sub-millisecond-latency data store. You will need a developer who understands Streaming and Queuing technologies, e.g. Kafka, AWS Kinesis, what data structures to use, how to improve concurrency, how to move data quickly between systems in microservices / pipelines and someone who already has functional experience of full-text search engine codes like Elasticsearch.

How do you design & ship a production code search engine like Bing?

It's been at least 15 years now since Yahoo! held the crown of search products, architecting search products or managing search infrastructure. A host of search engines outside Microsoft Bing, including Duck Duck Go Search, Baidu, Yandex and more computational engines like WolframAlpha make up Google's competition. Not to mention Tor search engines like Torch and Deep web search like notEvil Dark Web and Ecosia. To compete, you'll need to collaborate with Machine Learning (ML) and Natural Language Processing (NLP) data scientists with experience in interactive query-driven search engine technologies (like Elasticsearch, Lucene, and Solr), complex search logic and aggregations, who can develop large scale data pipelines and scalable infrastructure.

These ML / NLP researchers are the people who can build new search interfaces, data storage methods (and data warehouses like Google's BigQuery), develop pipelines, and infrastructure to scale search pipelines to tune search algorithms. The best Machine Learning freelancers are not easy to find but their applied knowledge can rank systems for billions of documents that will drive millions of search queries. Experience with Python, Flask, Postgres, NoSQL, AWS, Kubernetes, NLP, Spark, CI/CD, and other big data technologies. as well as document vectors and semantic search is vital.

On HostJane we seek to attract ML data scientists who have proven experience in applying tools for runtime profiling to optimize throughput and latency. Our FBH program has at least 2 data scientists who can establish comparative performance benchmarks and have experience with relevance tuning, document scoring, ranking, and cluster optimization.

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