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X This posting is for an existing vacancy.
Google utilizes AI tools to assist in assessing candidates in our hiring processes.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Waterloo, ON, Canada; New York, NY, USA; Sunnyvale, CA, USA.
Minimum qualifications: - Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 2 years of 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).
Preferred qualifications: - Master's degree or PhD in Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
About the jobGoogle'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.
In this role, you will be working as part of the GAWSS (GenAI Workspace Safety and Security) team that is responsible for building out and setting up mitigations. You will lead the team of developers on multiple critical AI/ML projects, including building LLM-based safety and security auto-raters, multiple critical classifiers to detect prompt injection attacks, and live traffic observability solutions for safety and security. You will collaborate with Google DeepMind (GDM) on new research-based defense techniques, and with other Product teams in Google to share and improve existing defences. You will also work closely with first-party teams across Workspace (Gmail, Chat, Drive, Meet, Calendar, etc) to ensure their AI features are protected.
AI will change the future of work in profound ways, and our products- Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Canada: $216000 - $222000 (CAD) 20% bonus target equity benefits.
Learn more about benefits at Google .
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) 20% bonus target equity benefits
Canada: $216000 - $222000 (CAD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Design, develop, test, deploy, maintain, and enhance large-scale software solutions.
- Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.
- Lead the development of the flagship Prompt Injection classifier.
