Staff Software Engineer, AI/ML

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience working with machine learning.
  
• 3 years of experience with Large Language Models (LLMs).
• Experience programming in Python.
• Experience with SQL, Data Analytics, and coLaboratory.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures/algorithms.
• 3 years of experience working in an organization involving cross-functional, or cross-business projects.

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.

Responsibilities

• Lead and direct the quality efforts for Web Guide, serving as a Team Lead for engineers in Zurich. Set priorities for the quality of work, ensuring alignment with the Mountain View team and driving key weekly meetings.
  
• Drive the implementation of AI-driven quality improvements for Web Guide. This includes prompting and distilling the latest Gemini models, writing AI raters, and performing an in-depth analysis of evaluations to launch improved product versions.
  
• Contribute directly to product development and maintain high code quality. Write production-ready code, participate in and lead design reviews, and provide constructive feedback on code developed by peers to ensure best practices, accuracy, testability, and efficiency.