Software Engineer III, AI/ML, Google Fi

Write product or system development code.Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.Participate in the development and delivery of AI/ML and agentic solutions for the product.Minimum qualifications:Bachelor’s degree or equivalent practical experience.2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.1 year 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), or specialization in another ML field.1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).Preferred qualifications:Master's degree or PhD in Computer Science or related technical fields.2 years of experience with data structures and algorithms.Experience developing accessible technologies.Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.Google Fi Wireless leverages the best of Google to deliver simple and secure mobile connectivity. Our team is responsible for the entire subscriber journey, from plan selection and device activation to providing award-winning coverage around the world. Our team's deep expertise spans cellular network operations, iOS and Android app development, and subscription business operations.The Fi team applies Google's AI to solve complex, real-world problems - from AI-enhanced call audio to AI billing summaries to AI-powered cohort analysis - that helps Google Fi customers stay reliably connected to what’s most important to them.The Fi team is committed to providing team members with the opportunity to build their applied AI skillset, so that all Fi subscribers can benefit from the best of Google's AI models.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $211000 (USD) + 15% bonus target + equity + benefitsLearn more about benefits at Google.Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Francisco, CA, USA.Bachelor’s degree or equivalent practical experience.2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.1 year 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), or specialization in another ML field.1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).