Software Engineer III, GenAI Data Operations Research, XR

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.

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,)
Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
Lead high-volume synthetic datasets including metadata deliveries for XR and Platform and Devices (P&D) projects.
Build modular toolkits for GenAI bulk inference and metadata extraction.
Develop end-to-end pipelines for fine-tuning in-house foundational models.

Minimum qualifications:

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 one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).

Preferred qualifications:

Master's degree or PhD in Computer Science or related technical fields.
2 years of experience with data structures and algorithms.
Experience with C++, Parallel Computing, Blender.
Experience developing accessible technologies.
Proficiency in Python and experience with frameworks for large-scale data processing.