Staff Software Engineer, Content Safety

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.

In this role, you will be responsible for setting technical direction for the Singapore-based team, and will collaborate with technical leadership throughout the global organization. You will be creating a collaborative engineering culture for the new site, and align the team’s work with organization priorities. You will collaborate with colleagues across North America, Europe and Latin America (LATAM). You will be accountable for delivering quality, future-proof and performant content safety solutions that combine content safety protection with production-grade infrastructure. You will protect users from exposures to offensive, sensitive or 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 the users.The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

Responsibilities

• Safeguard business-critical products that represent business growth, market share or value to Google, including Generative Artificial Intelligence (GenAI)-based server-side and on-device experiences.
• Design, build, maintain and scale content safety solutions (e.g., classifiers, multimodal understanding) to make quality users experience.
• Work on projects such as agentic workflows for threat understanding and content moderation.
• Lead the design and implementation of solutions in specialized Machine Learning (ML) areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.

Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 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 a related ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with testing, and launching software products, and 3 years of experience with software design and architecture.

Preferred qualifications:

• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role with leading project teams and setting technical direction.
• Experience in content safety, as applied to software products.
• Experience in responsible AI or safety-adjacent fields, such as factuality, or product policy.
• Experience in scaling pipelines, deploying systems, and designing defensive architecture to meet Service Level Objectives (SLOs).
• Knowledge of machine learning and Large Language Models (LLMs) working, and transformers, activations, and how to train and deploy them.