Senior Software Engineer, AI/ML GenAI, Core

Google•Kirkland, WA

1d•$174,000 - $252,000

About The Position

Google software engineers develop technologies used by billions of people to connect, explore, and interact with information. Engineers work on projects critical to Google and may move between teams and projects as business needs evolve. The role calls for versatility, leadership, and enthusiasm for solving problems across the full stack. The Core team builds the technical foundation behind Google’s flagship products, including underlying design elements, developer platforms, product components, and infrastructure. The team creates central solutions across Google products, removes technical barriers, strengthens existing systems, and influences important technical decisions across the company. This role focuses on designing and implementing generative AI solutions, using machine-learning infrastructure, and evaluating tradeoffs among techniques and application domains. Individual pay is determined by job-related skills, experience, and relevant education or training. The listed U.S. compensation is $174,000–$252,000, plus a 15% bonus target, equity, and benefits.

Requirements

Bachelor’s degree or equivalent practical experience.
5 years of experience programming in Python or C++.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
3 years of experience with end-to-end machine learning, such as model deployment, model evaluation, data processing, or debugging.
1 year of experience with state-of-the-art GenAI techniques, such as LLMs, multimodal systems, or large vision models, or with GenAI-related concepts such as language modeling or computer vision.

Nice To Haves

Master’s degree or PhD in Computer Science or a related technical field.
5 years of experience with data structures and algorithms.
1 year of experience in a technical leadership role.
Experience developing accessible technologies.

Responsibilities

Write and test product or system development code.
Collaborate with peers and stakeholders through design and code reviews to promote best practices, including style guidelines, code submission, accuracy, testability, and efficiency.
Contribute to documentation or educational content and adapt it based on product or program updates and user feedback.
Triage product or system issues and debug, track, and resolve them by analyzing sources and impacts on hardware, network, or service operations and quality.
Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between techniques and their application domains.