Staff Software Engineer, Content Safety, Infrastructure
Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Preferred qualifications:
- 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.
- Experience in content safety, as applied to software products.
- Experience in scaling pipelines, deploying global-scale systems, and designing defensive architecture to meet Service Level Objectives (SLOs).
- Experience in Responsible AI or safety-adjacent fields, such as factuality, or product policy.
- Understanding of both machine learning and how large language models (LLMs) work including high-level concepts of transformers, activations, and how to efficiently train and deploy them at scale.
About the job
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.
As a Staff Software Engineer, you will be responsible for setting technical directions for our Singapore-based team, and collaborating with technical leadership throughout the broader global organization. You will be a creating a productive and collaborative engineering culture for our new site, and align your team’s work with organization priorities. You will collaborate with colleagues across North America, Europe and LATAM.
In this role, you will be accountable for delivering high-quality, future-proof and performant content safety solutions that combine content safety protection with production-grade infrastructure. You will protect users from exposure to offensive, sensitive or potentially harmful content, and unlock new opportunities for the business. You will be contributing to the success of product experiences, both server-side and on-device, by making them safer for our users.
Responsibilities
- Safeguard business-critical products that represent significant business, market share or strategic value to Google, including GenAI-based experiences both server-side and on-device.
- Design, build, maintain and scale content safety solutions (e.g., scalable classifiers, multimodal understanding) to make users’ experiences safer.
- Work on projects such as agentic workflows for threat understanding and content moderation.
- Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
- 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.