Software Engineer III, Generative AI

Requirements:

• 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 core GenAI concepts (e.g., LLM, Multi-Modal, Large Vision Models) and experience with text, image, video, or audio generation.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Nice to Haves:

• Master's degree or PhD in Computer Science or a related technical field.
• 2 years of experience with data structures or algorithms.
• Experience building applications for enterprise needs, including AI safety, data residency, integration with existing systems, and return on investment.
• Experience developing accessible technologies.
• Familiarity with technologies such as artificial intelligence/machine learning (AI/ML) or large language models (LLMs).
• Understanding the unique needs of Cloud customers and effectively bridge the gap between AI technology and real-world use cases outside of Google.

What You'll be Doing:

• Write a 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.
• Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.

Perks and Benefits:

• Google's next-generation technologies that change how billions of users connect, explore, and interact with information and one another.
• Opportunities to work on critical projects with the flexibility to switch teams and projects.
• Work on challenging problems across the full-stack in a fast-paced environment.