We need an experienced backend engineer with a passion for building large scale distributed systems to enable more innovations on the search, recommendation, and AI services and products. We look for passions in designing and developing cutting-edge techniques such as Large Language Models (LLM), Ranking, Index Serving in large scale like 100K+ nodes by collaborating with ML/AI data scientists.
Bing Fundamentals focuses on providing a search and recommendation platform for Microsoft internal partners using the documentation recall and reranking backend service suite. As a team, we manage one of the world’s largest distributed systems and have experienced great success in building efficient large scale distributed systems for search. Now, the team has a per decade rare opportunity to simplify the serving stack, to serve the biggest index in the most efficient way, and to drive up the relevance innovations with advanced deep learning and Large Language model techniques. The agility of engineering and deployment also presents as a big challenge when handling such a complex system. As Bing embraces the newest LLM innovations, the need for IndexServe to build up AI intelligence is becoming bigger.
Within Bing Fundamentals, we are the IndexServe team, and we have the exciting responsibility of trying to tackle these challenges. As a team, we are trying to build the most agile, performant, stable, experientable yet efficient index serving platform. On this platform, relevance techniques can be quickly implemented, iterated, qualified and flighted to evaluate their customer impacts with convenience while full-funnel debuggability. The same platform also provides all the cutting edged techniques and utilities, like deep learning, machine learning, LLM, C# rankers. It has the most advanced AI toolset for our scientists to innovate, and for our products to serve the most relevant documents.
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