Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  
• 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• Experiences in Search quality or Search related products.
• Experiences in recommendation and ranking systems.
• Experiences in GenAI, LLM, machine learning algorithms and tools.

About the job

Play Store serves billions of users and helps them search and discover useful, relevant, and high quality content. Play Search is a critical product for Play’s growth, Google business, and Android ecosystem. Search Gateway and Off-Store Search are the entry points of Play Search, and include Search Home, Play Suggest, Voice Search and App Universal.

As a Software Engineer, you will contribute to design, development, and improvement of back-end services and features that power Play Store's search and discovery experience. You will have the opportunity to work on highly scalable systems, implement new features, run large-scale A/B test experiments to enhance user experience on Search Homepage and Suggest, including the application of Machine Learning and Generative AI - ultimately impacting the search experience of billions of users.

Responsibilities

• Design, develop and improve scalable solutions for the Play Store Search Homepage and Suggest features, impacting billions of Android users globally.
• Implement backend services and APIs within the Play Gateway Server infrastructure, contributing to features that impact millions of users.
• Contribute to enhancing algorithms and models for query suggestions and personalized content by leveraging technologies like LLMs and DNNs, under the guidance of executive engineers.
• Analyze user engagement data and experiment results (A/B tests) to help measure impact and identify opportunities for improvement.
• Collaborate with Product Managers, UX Designers, and other engineering team members to understand requirements and deliver high-quality code.