Software Engineer II, AI/ML
Summary
Software Engineer II on Google's People Operations Engineering team, building AI platform tooling and intelligent systems that power Google's internal talent lifecycle and enterprise productivity. Day-to-day involves writing production code, participating in design/code reviews, maintaining documentation, and debugging large-scale AI/ML and distributed systems.
In People Operations Engineering (POps Eng), we build the intelligent systems, workflows, and core tooling that power Google’s talent lifecycle and enterprise productivity. Our team bridges research with production-grade software engineering to solve complex organizational problems at Google scale by providing reusable, robust AI platform tooling and Artificial Intelligence (AI) data, to create a connected AI ecosystem that enables enterprise-scale delightful agentic experiences for Google employees.
At Corp Eng, we build world-leading business solutions that scale a more helpful Google for everyone. As Google’s IT organization, we provide end-to-end solutions for organizations across Google. We deliver the right tools, platforms, and experiences for all Googlers as they create more helpful products and services for everyone. In the simplest terms, we are Google for Googlers.
- Write product or system development code.
- 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).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 1 year of experience with data structures and algorithms.
- Experience in one or more areas of Machine Learning, such as AI algorithms, AI platforms, or Generative AI Agents.
- Experience with distributed processing and distributed systems.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- Experience in AI Algorithms, Clustering Algorithms, Machine Learning Algorithms, GraphQL, Knowledge Graph.
- Experience developing accessible technologies.