Senior Software Engineer, GenAI GCP Security

Google•Kirkland, WA

22h•$174,000 - $252,000

About The Position

Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Requirements

Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
5 years of experience programming in Python or C++.
3 years of experience with machine learning (ML) infrastructure (e.g., model deployment, model evaluation, optimization, data processing, or debugging).
1 year of experience with Generative AI (GenAI) techniques (e.g., Large Language Models, Multi-Modal, Large Vision Models) or GenAI-related concepts (e.g., language modeling, computer vision).
1 year of experience with software design, architecture, and machine learning.

Nice To Haves

Master's degree or PhD in Computer Science, or a related technical field.
5 years of experience developing cloud-based storage systems.
5 years of experience with data structures and algorithms in a data ML-focused role.
2 years of experience with security engineering, computer and network security.
Experience working on Google Cloud Platform (GCP).

Responsibilities

Write and test 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.
Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.