Join Google's innovative Cloud AI team as a Staff Software Engineer specializing in Document Understanding. You will be instrumental in developing cutting-edge technologies that shape how billions interact with information. This role offers the chance to contribute to massive-scale products, bringing fresh ideas in areas like AI, NLP, and distributed systems. Embrace opportunities to evolve your skills across full-stack challenges as our fast-paced business grows.

This position focuses on advancing document understanding and processing through agentic loops and fine-tuned open-source models. The Google Cloud AI Research team tackles complex AI challenges to benefit diverse industries such as tech, healthcare, finance, and retail. We are dedicated to pushing the boundaries of AI research and collaborating with product teams to deliver impactful real-world solutions for our customers.

Design, develop, test, deploy, maintain, and enhance large-scale software solutions. Provide technical leadership for high-impact projects, managing priorities, deadlines, and deliverables. Ensure team alignment and clarity on goals, outcomes, and timelines, influencing and coaching distributed engineering teams. Spearhead the design and implementation of solutions within specialized ML domains, optimize ML infrastructure, and guide model optimization and data processing strategies. Lead software engineering teams in building novel solutions for document processing.

A Bachelor's degree or equivalent practical experience is required. Minimum of 8 years of experience in software development is essential. 5 years of experience in testing and launching software products, along with 3 years in software design and architecture. Possess 5 years of experience in one or more of the following: Speech/audio technologies, reinforcement learning, ML infrastructure, or another ML specialization. Demonstrate 5 years of experience with ML design and ML infrastructure, including model deployment, evaluation, data processing, debugging, and fine-tuning. Experience integrating generative AI tools or LLM interfaces into workflows is necessary.

Preferred qualifications include a Master's degree or PhD in a related technical field, 8 years of experience with data structures and algorithms, 3 years in a technical leadership role, and 3 years of experience in complex, matrixed organizations.