Senior Software Engineer, AI-Enhanced Data Insights and Infra

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in the Python programming language.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience with database design and performance analysis.
• 3 years of experience in an engineering productivity environment.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 1 year of experience in a technical leadership role.
• Experience developing and maintaining Angular applications.
• Experience developing and deploying AI/ML solutions, including experience with LLMs and anomaly detection.
• Experience with BOQ for deployment and improved reliability.
• Experience with SQL and database technologies, preferably Spanner and with data analysis and visualization tools (e.g., Awesomecharts, Colab, PLX).

About the job:

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.

In this role, you will be responsible for building a unified platform that provides actionable insights from device test data, covering Pixel phones, wearables, and hearables. You will expand the platform's capabilities, adding new testing domains, and developing cutting-edge AI/ML solutions to automate and improve the data analysis and reporting.

This is a unique opportunity to shape the future of device testing, drive innovation with AI/ML, and leave a lasting impact on Google's product quality. You will develop a broad range of skills, gain valuable experience, and have a clear path for career advancement within a dynamic and innovative environment.

The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities:

• Design, develop, and optimize data processing pipelines for new and existing metrics. Ensure data accuracy and reliability through robust validation processes, and collaborate with test engineers on data requirements.
• Develop and maintain an intuitive Angular-based UI for data visualization and reporting. Create and enhance dashboards, charts, and other visualizations, and ensure UI performance and user-friendliness.
• Develop and implement AI/ML solutions for automated data analysis and reporting (including LLMs). Build anomaly detection models for performance issue identification, and experiment with AI/ML to optimize data processing.
• Maintain and improve backend and frontend systems. Ensure code quality and address technical debt. Collaborate with cross-functional teams. Document new features and update existing documentation.