Software Engineer, AI for Large-Scale Systems

Mid • On-site

$141,000 - $202,000/yr

Kirkland, WA

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 ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models) and experience with text, image, video, or audio generation.
2 years of experience with software development in C++ programming languages.

Preferred qualifications:

Master's degree or PhD in Computer Science or related technical fields.
2 years of experience with data structures or algorithms.
Understanding of distributed systems and their operational issues.

About the job

The AI for Large Scale Systems (AILS) team in Core Data aims to transform the design, development, and operation of large-scale infrastructure systems through the innovative application of Artificial Intelligence.

Our mission is to leverage AI to address key issues in building and maintaining large, complex software systems. This includes dramatically improving AI-assisted code generation, especially within Google's extensive and intricate codebases where knowing where to even begin is a challenge. We are also focused on using AI to enhance code quality, improve system reliability, and deepen our understanding of system behavior. We aim to build tools and agents that assist engineers in producing correct, well-tested, bug-free, and maintainable code, as well as in operating these systems effectively.

The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

Enhance and productionize the Glimpse codebase indexing system to improve AI understanding and code generation capabilities within large Google projects.
Develop and prototype AI-driven tools and agents to improve code authoring.
Contribute to the development of AI-powered tools for code quality and reliability.
Collaborate with engineers and researchers across Core Data and other parts of Google to identify opportunities, deploy solutions, and measure impact.
Contribute to benchmarks and evaluations for AI coding agents and tools.

Google

Google LLC started as a PhD project by Larry Page and Sergey Brin in 1998 at Stanford University. Google LLC has blossomed into a behemoth of the tech world. With its mission to organize the world's information and make it universally accessible and useful, Google’s search engine is its crown jewel. Online advertising, via AdWords and AdSense, forms the backbone of its financial success. Beyond search, Google has ventured into cloud computing, hardware, and software development. The innovative PageRank algorithm revolutionized search engine technology, and surviving the dot-com bubble burst and going public in 2004 spurred its meteoric growth. Acquiring YouTube stands as a testament to Google’s strategic expansion.