Software Engineer III, Generative AI Safety

• Contribute to the development and implementation of systems that detect and prevent abuse across DeepMind products.
• Design, build, and maintain components of our account-centric abuse detection systems on the GenAI Safety Platform.
• Analyze data to understand abuse patterns and improve the effectiveness of our detection methods and writing and testing production-quality code, and participating in code reviews.
• Work with partner teams (e.g., Trust and Safety, Product Managers) to understand requirements and translate them into technical solutions.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 2 years of experience with software development in one or more programming languages (e.g., Python, C++, Java, Go).
• Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
• Experience with data structures and algorithms.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• Experience with AI development, agentic workflows, and applying machine learning concepts to real-world applications.
• Hands-on experience building anti-abuse systems, fraud detection mechanisms, or security solutions, with a solid understanding of account security and identity concepts.
• Proven track record of designing, building, and deploying large-scale systems and high-throughput data processing pipelines using tools such as SQL or Flume.
• Excellent problem-solving and investigative skills.

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 2 years of experience with software development in one or more programming languages (e.g., Python, C++, Java, Go).
• Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
• Experience with data structures and algorithms.