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.
As a Software Engineer in the GenAI stream, you will architect and scale the critical infrastructure required for GenAI data generation and inference tasks. You will develop production-ready pipelines for at-scale data processing using distributed computing frameworks, run and monitor large-scale deep learning experiments, and leverage JAX to establish end-to-end pipelines for fine-tuning foundational models. Your work will involve delivering synthetic datasets for key Android XR projects, integrating and advancing human-centric generative pipelines. Additionally, you will integrate automated evaluation tools and filtering stages to ensure data diversity and quality, bridging the gap between advanced research and production-ready applications.
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
- Build scalable infrastructure and modular toolkits for at-scale distributed data processing, GenAI data generation, and metadata extraction.
- Run, monitor, and scale deep learning experiments across compute clusters, and develop efficient inference pipelines using JAX.
- Lead high-volume synthetic datasets including metadata deliveries for XR and device projects.
- Integrate automated evaluation and filtering tools to measure domain gaps and ensure high-quality, photorealistic data.
- Migrate pipelines to specialized hardware accelerators (like TPUs or GPUs) for efficient production-scale inference.
Qualifications
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.
- Experience in architecting infrastructure for bulk inference and metadata extraction.
- Exposure to or direct experience working with human-centric generative pipelines.
- Proficiency in Python and experience with frameworks for large-scale data processing.
- Ability to enable end-to-end fine-tuning for foundational GenAI models and optimize them for production environments, including specialized hardware like TPUs.