Qualifications

Minimum qualifications:

• Bachelor\'s degree or equivalent practical experience.
  
• 8 years of experience in software development, and with data structures/algorithms.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  
• 5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
  

Preferred qualifications:

• Master\'s degree or PhD in Computer Science, Machine Learning, Natural Language Processing, Information Retrieval, a related technical field, or equivalent practical experience.
  
• Experience launching and scaling user-facing, large-scale, production quality systems.
  
• Excellent software development skills, with the ability to design, implement, and optimize high-performance systems in a complex, distributed environment.
  
• Passion for machine learning technologies, and background in ML/NLP/Quality.
  

Summary

• Bachelor\'s degree or equivalent practical experience.
  
• 8 years of experience in software development, and with data structures/algorithms.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  
• 5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
  

Description

Google Cloud\'s software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud\'s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

We are building intuitive and effective searching and finding experiences by enabling search journeys that bridge across Workspace products (e.g., Gmail, Chat, Drive, etc.). We have an ambitious roadmap for making Workspace Search excellent, including the usage of advanced Machine Learning (ML) technologies, significant user-facing changes, revamping our evaluation framework and more. We are embarking on a major shift from token based search to embedding based search to support some of the cutting edge use cases (e.g., natural language, multi modal, etc).

As an Engineer for the Workspace Search Quality, you will have the opportunity to make a significant impact on the way people use Workspace Search across Gmail, Drive, Chat, etc.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• Lead the design and implementation of search solutions, from understanding natural language queries to developing and deploying machine learning models that significantly improve search quality.
  
• Drive innovation by exploring and integrating cutting-edge machine learning techniques, algorithms, and architectures to enhance search relevance and user experience.
• Own the technical goal for critical areas of Workspace Search, collaborating with cross-functional teams to define and deliver on a strategic roadmap.
• Mentor and guide a team of engineers, fostering a culture of technical excellence, collaboration, and continuous learning.
  
• Establish and refine evaluation frameworks and metrics to measure and track progress against key performance indicators.