
Organizing the world's information and making it universally accessible.
Software Engineer II, Neural Retrieval
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Write product or system development code. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
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Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
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Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
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Improve embedding retrieval quality with better training data, improved and creative recipes.
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Help build a retrieval system that scales to these domains with minimal engineering effort, allows quick evaluation and user facing turnaround time.
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As part of Search Platforms, the Neural Retrieval team's mission is to provide possible inputs to Large Language Models (LLM) Search products.
We are working directly with client teams to build Retrieval-augmented generation (RAG) solutions that scale across Google, based on the latest LLM advances in embeddings and combining them with structured data approaches (like SQL-based retrieval). The team is looking to harness the power of agents and latest LLM frontier to scale to new domains, while significantly advancing developer speed, quality and cost of retrieving the most helpful content. We are building on top of and working closely with Core IR (Retrieval Engine) and Gemini Encoder Heavy and Embeddings to deliver impact across Search.
Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
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Bachelor’s degree or equivalent practical experience.
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1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
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1 year of experience with data structures and algorithms.
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1 year of experience implementing core ML concepts.
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Googleについて

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
従業員数
Mountain View
本社所在地
$1,700B
企業価値
レビュー
10件のレビュー
4.5
10件のレビュー
ワークライフバランス
3.2
報酬
4.3
企業文化
4.1
キャリア
4.2
経営陣
3.8
82%
知人への推奨率
良い点
Great benefits and perks
Innovative and interesting work
Career development and learning opportunities
改善点
High pressure and expectations
Long hours and heavy workload
Fast-paced and overwhelming environment
給与レンジ
57,503件のデータ
Mid/L4
Mid/L4 · Accessibility Analyst
1件のレポート
$214,500
年収総額
基本給
$165,000
ストック
-
ボーナス
-
$214,500
$214,500
面接レビュー
レビュー9件
難易度
3.4
/ 5
期間
14-28週間
内定率
44%
体験
ポジティブ 0%
普通 56%
ネガティブ 44%
面接プロセス
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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