Software Engineer II, ML Experimentation

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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 or algorithms.
  
• 1 year of experience with full stack development, across back-end such as Java, Python, GO, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
  

Preferred qualifications:

• Master's degree in Computer Science or related technical field.
• Experience in ML model coding languages (e.g., Python).
• Experience with distributed systems and scheduling infrastructure.

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.

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

• Support the shift to Generative AI, leveraging development led by Google DeepMind.
• Drive improvements in researcher and ML developer productivity.
• Enable new ML use cases through advancements in internal tooling and scheduling infrastructure.
• Identify and execute new projects to accelerate AI at Google scale.