Senior Engineering Analyst, AI Safety

The AI Safety Protections team within Trust and Safety develops and implements AI/LLM-powered solutions to ensure the safety of generative AI foundational models. This includes Gemini, Nano Banana, Veo, Agents and Robotics, working with Google DeepMind, as well as downstream GenAI products etc.

We are a team of passionate data scientists and machine learning experts dedicated to mitigating risks associated with Generative AI. As a member of our team, you will have the opportunity to apply the latest advancements in AI/LLM, work with teams developing AI technologies, as well as protect the world from real-world harms.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Develop scalable safety solutions for AI products across Google by leveraging advanced machine learning and AI techniques.
• Apply statistical and data science methods to thoroughly examine Google's protection measures, uncover potential shortcomings, and develop actionable insights for continuous security enhancement.
• Drive business outcomes by crafting compelling data stories for a variety of stakeholders, including executive leadership.
• Provide technical leadership by fostering growth and ensuring success of team members through targeted mentorship and guidance.
• Work with sensitive content or situations and may be exposed to graphic, controversial, or upsetting topics or content.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
• 5 years of experience in data science.
• Experience with programming languages (e.g., Python, R, Julia), database languages (e.g., SQL), and scripting languages (e.g., C/C++, Python, Java).

Preferred qualifications:

• MBA, or Master's degree in a quantitative discipline (e.g., Statistics, Operations Research, Economics, Biology, Computer Science, Mathematics, Physics, Industrial Engineering, etc.).
• Experience in abuse and fraud disciplines, especially focused on web security, harmful content moderation and threat analysis.
• Experience in applying machine learning techniques to large datasets.
• Experience with prompt engineering and fine-tuning Large language Models (LLMs).
• Excellent written, verbal, and presentation skills to effectively communicate with a variety of stakeholders, including executive leadership.
• Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.