Software Engineer II - Artificial Intelligence and Machine Learning

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  
• 1 year of experience with data structures and algorithms.
• 1 year of experience implementing core ML concepts.
  

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• Experience building automated systems with LLMs and agentic workflows.
• Experience with distributed systems, big data processing, ML modeling, data science.
• Experience as a generalist software engineer and with full stack, (backend and frontend and applied ML).
• Interest/experience applying AI/ML and LLMs to abuse detection.

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.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Responsibilities

• Write product or system development code. 
  
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  
• 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.
  
• Apply foundational ML concepts and contribute to the implementation of solutions in one or more specialized ML areas.