Software Engineer III, Google Security Operations, AI/ML

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.).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.Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.Design, develop, and deliver high-quality code for security products and systemsMinimum 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.Experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).Experience in full-stack software development, including designing, developing, and deploying end-to-end applications.Experience with Machine Learning frameworks (e.g., TensorFlow, PyTorch, or JAX) and applying machine learning algorithms to solve technical or business problems.Preferred qualifications:Master's degree or PhD in Computer Science or related technical fields.2 years of experience with data structures and algorithms.2 years of experience with C#, TypeScript, and Angular.Experience developing accessible technologies.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. We exist in order to enable security analysts to fight evil in the fastest and most efficient manner. We are here to bridge the gap in Google's security tooling and drive Google towards a unified Security Operations (SecOps) by implementing Managed Defense features and more in Security Orchestration, Automation and Response (SOAR) Case Management. We are a critical group within Google Cloud SecOps focused on the SOC Analyst Experience, building the core tools that security professionals use for response, case management, and alert investigation.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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefitsLearn more about benefits at Google.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.Experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).Experience in full-stack software development, including designing, developing, and deploying end-to-end applications.Experience with Machine Learning frameworks (e.g., TensorFlow, PyTorch, or JAX) and applying machine learning algorithms to solve technical or business problems.