Software Engineer III, AI/ML GenAI, YouTube

Google•Mountain View, CA

5h•$147,000 - $210,000

About The Position

Google software engineers develop technologies used by billions of people to connect, explore, and interact with information. Engineers work on projects critical to Google’s needs and may move between teams and projects as the business evolves. The role calls for versatility, leadership qualities, and enthusiasm for solving problems across the full stack. This position is with YouTube, where teams work to help people share their stories, explore their interests, and connect with one another. The work combines technology and creativity to develop products that help people see and understand the world. Individual pay is determined by job-related skills, experience, and relevant education or training. The listed US compensation is $147,000–$210,000, with a 15% bonus target, equity, and benefits.

Requirements

Bachelor’s degree or equivalent practical experience.
2 years of experience programming in Python and C++.
1 year of experience with end-to-end machine learning, such as model deployment, model evaluation, data processing, or debugging.
Experience with core GenAI concepts, including LLMs, multimodal systems, and large vision models, and experience with text, image, video, or audio generation.

Nice To Haves

Master’s degree or PhD in Computer Science or a related technical field.
2 years of experience with data structures and algorithms.
Experience developing accessible technologies.

Responsibilities

Write product or system development code.
Collaborate with peers and stakeholders through design and code reviews to ensure best practices, including style guidelines, code check-in, accuracy, testability, and efficiency.
Contribute to existing documentation or educational content and adapt it based on product or program updates and user feedback.
Triage product or system issues and debug, track, and resolve them by analyzing causes and impacts on hardware, network, or service operations and quality.
Implement GenAI solutions, use ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.