Staff Software Engineer, Android Agent
In most instances, this position requires in-person interviews as part of the hiring process.Minimum qualifications:
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 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).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
- Design, build, and optimize the end-to-end machine learning systems and models that power Android's next-generation AI agent.
- Translate ambiguous user needs and product goals for agentic AI into well-defined technical problems and innovative ML solutions.
- Architect and implement robust data pipelines for collecting, cleaning, and processing the massive datasets required for training and fine-tuning ML models.
- Lead the development, training, and continuous improvement of core machine learning models, with a focus on on-device performance and user privacy.
- Establish and own the evaluation frameworks to rigorously measure model quality, ensuring our AI features are reliable, helpful, and personalized.
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