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:- 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.
- 2 years of experience with technical innovation in data governance or related fields.
- Experience with machine learning and privacy data handling.
Responsibilities - Lead the design and architecture of highly complex ML pipelines and distributed systems, ensuring they meet long-term scalability and reliability goals.
- Drive the adoption of next-generation AI/ML techniques to solve ambiguous, high-impact business problems, moving from conceptual prototypes to global production.
- Set the "gold standard" for code quality, testing, and deployment within the team, performing deep-dive architectural reviews and optimizing system performance.
- Mentor executive and mid-level engineers, fostering a culture of technical growth, and represent the team in high-level technical discussions across the broader organization.
- Partner with researchers to operationalize models and work with product stakeholders to align technical roadmaps with user needs.
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
Learn more about benefits at Google .
