Software Engineer, GenAI, DeepMind

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

As a Senior Staff Software Engineer for AI/ML Security, you will serve as the primary technical visionary for Model Armor and Sensitive Data Protection, supporting the strategy to secure LLMs against prompt injection, jailbreaking, and data exfiltration. You will manage architectural issues by integrating filter-based defenses into scalable, observable, and explainable distributed systems that protect enterprise customers at Google Cloud scale. Beyond technical execution, you will navigate extreme ambiguity to drive overarching business strategy and lead high-stakes, cross-Google initiatives. You will have a master-level ability to negotiate and forge consensus among researchers and engineers, translating security goals into measurable, high-impact solutions for the generative AI era.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities

• Develop a wide range of solutions, spanning from modeling to infrastructure (e.g., storing new knowledge, efficiently using LLMs to evaluate thousands of requests, improving those models, and enhancing their intelligence).

• Work with multiple codebases and machine learning libraries, creating numerous throwaway models and prototypes, as well as reusable model architectures and advanced libraries.

• Work in the context of real applications for important Google products and in partnership with product teams and other research engineers.

• Develop novel and practical solutions for AI and AI-powered tools. Expect to work on ambiguous, ill-defined problems, move quickly, iterate rapidly, and handle complex problems and codebases.

Qualifications Minimum qualifications:

• Bachelor's degree in Computer Science, a relevant technical field with a focus on AI research, or equivalent practical experience.

• 8 years of experience in the full lifecycle of research modeling.

• Experience working with two or more of the following: advanced algorithms, machine learning, information retrieval, natural language processing, data science, distributed and parallel systems, developing software systems.

Preferred qualifications:

• Ability to solve exceptionally complex problems (e.g., math and programming competitions or developing novel algorithms).

• Exceptional hacking skills and ability to quickly prototype and iterate on complex systems.

• Passion for working on real problems, a determination to overcome obstacles, and the ability to work on any task to get the job done.

• Quick learner with strong analytical and coding skills.

• Willingness to learn multiple tools and codebases.

• Willingness to work on ambiguous, ill-defined problems, refining final goals as new information is learned.