Software Engineer, Exploration and Refinements Quality

scale data processing pipelines, machine learning for real-world problems, balancing the needs of many downstream clients, collaboration across teams and timezones.

About the job

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 Refinements Quality team creates user-driven frameworks that offer clear guidance and inspiration throughout their journeys. They construct a data infrastructure that prioritizes both seamless performance and the capacity to support future product development.

In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities

• Execute focused subtasks within a broader project, with tasks assigned by management or executive team members.

• Aim for high-quality work within a short timeframe.

• Select from existing solutions to familiar technical problems, escalating complex issues to executive members.

• Collaborate with the larger team through knowledge sharing and cross-functional contributions.

• Contribute to existing data pipelines, focusing on data ingestion, cleaning, preprocessing, and feature engineering with an emphasis on modern machine learning techniques like embeddings. Collaborate with team members to refine pipeline components, select appropriate data storage solutions, and escalate any complex issues that arise.