Software Engineer, Applied AI, Pixel

Software Engineer, Applied AI

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. In this role, you will select, evaluate, and fine-tune state-of-the-art AI models to develop innovative, user-facing features in Pixel software, owning the entire model-to-feature lifecycle. You will design and implement robust evaluation pipelines and metrics to rigorously measure model quality, performance, and readiness for on-device deployment.

Your role will require you to collaborate closely with research scientists, product managers and application engineers to understand feature requirements and translate them into specific model capabilities and fine-tuning strategies. Additionally, you will contribute to a culture of engineering and scientific excellence through detailed design/code reviews, collaborating with peers and upholding best practices for model development, and clearly communicating your findings and recommendations on model selection and performance to your team and direct stakeholders to inform technical and product decisions.

Responsibilities:

• Contribute to the strategy for selecting, fine-tuning, and deploying foundational models to achieve specific product goals.
• Work on the deployment and optimization of large language models (LLMs) and multi-modal models for both on-device and cloud execution. This includes leveraging and improving ML infrastructure for model evaluation, data processing, and debugging.
• Contribute to the design and implementation of data collection and processing solutions.
• Develop evaluation frameworks to measure the real-world performance and impact of machine learning models on the user experience.
• Stay current with the latest advancements in Generative AI.
• Translate cutting-edge research into tangible product features that create transformative and helpful experiences for Pixel users.