Senior Software Engineer AI/ML, Content Safety Applications

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
• 3 years of experience testing, maintaining, or launching software products.
• 1 year of experience with software design and architecture.

Preferred qualifications:

• Experience with the LLM ecosystem or Agentic Frameworks.
  
• Experience with Generative AI technologies and their associated risks and opportunities.
• Knowledge of machine learning algorithms, including supervised and unsupervised learning, deep learning, reinforcement learning, and generative AI.
• Familiarity with the machine learning development lifecycle, including data pre-processing, model training, evaluation, and deployment.
• Familiarity with trust and safety, content safety, or responsible AI domains, with an understanding of adversarial dynamics, content moderation tests, or similar safety-adjacent fields.

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 part of a global team, you will lead the full lifecycle of projects that protect Google's users and business-critical products, including our latest generative AI experiences. You will be responsible for designing, building, and scaling the next generation of our threat intelligence and content safety solutions.

You will be accountable for delivering high-quality, future-proof and performing infrastructure, and your work will protect users from exposure to offensive, sensitive or potentially harmful content. You will be joining our existing team in São Paulo, contributing to the success of Content Safety engineers working in Agents, Classifiers and Applied AI efforts.

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:

• Develop the infrastructure for running AI-based protections/classifiers, from initial problem definition and data acquisition through to model configuration, deployment, and long-term maintenance.
• Collaborate effectively with cross-functional and cross-regional (San Francisco/Dublin) teams of software engineers, product managers, and business stakeholders to deliver impactful safety solutions. 
• Stay current with the latest advancements in AI research, translating new techniques into practical applications for real-world safety issues.
• Contribute to the team's technical strategy and architecture, helping to guide our approach to building scalable AI features and infrastructure.