Senior Staff Engineering Analyst Manager, Gemini, NanoBanana, Veo

In this role, you will apply the latest advancements in AI, collaborating with experts and leadership across DeepMind, Core, and Trust and Safety to develop model mitigations that protect users worldwide.The US base salary range for this full-time position is $237,000-$329,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Lead and scale a team of engineering analysts focused on Introspection and post-training; develop the next wave of leaders through technical mentorship and guidance.
• Pioneer the use of technology (Introspection, supervised fine tuning, direct preference optimization, develop encoder systems, etc.) and design safety mitigations architectures.
• Drive cross-functional alignment across DeepMind and Trust and Safety stakeholders, and lead executive communications, design, and metrics reviews.
  
• Direct the strategy for foundational model launches (e.g., Gemini, GemPix, Veo, etc.).
• Apply statistical and data science methodologies to audit model safety and uncover vulnerabilities, ensuring continuous security enhancement through insights.
  

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience in data science or machine learning.
• 8 years of experience in data analysis using SQL and scripting languages (e.g., Python).
• 5 years of experience in technical leadership or people management.

Preferred qualifications:

• Master's degree in a quantitative discipline.
  
• Experience applying machine learning/large language models (LLMs) in industry settings.
  
• Experience with prompt engineering and fine-tuning LLMs.
• Excellent written, verbal, and presentation skills to effectively communicate with a variety of executive level stakeholders.
• Excellent problem-solving and critical thinking skills with an interest in new technology in an ever-changing environment.