Staff Software Engineer, Android Trust

• Own critical areas of Android Ecosystem safety.
  
• Lead the design, develop, deploy and maintain large scale engineering systems in the area of counter abuse.
  
• Lead the design, development and deployment and scale ML and AI models, including Large Language Models (LLMs) and Generative AI (GenAI) aimed at protecting the users, developers and other stakeholders of the Android ecosystem.
• Provide technical leadership on high-impact projects. Manage project priorities, deadlines and deliverables. Influence and mentor a distributed team of engineers.
  
• Work in a high paced environment with multiple partner stakeholders and have the ability to adapt to a fast changing regulatory environment.
  

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 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 another ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

• PhD degree in Computer Science, Engineering, or a technical related field.
• 8 years of experience with data structures and algorithms.
• Experience working in the area of safety, security, privacy, and counter-abuse.
• Experience with AI/ML modeling for classification and system automation.

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 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 another ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows.