Senior Software Engineer, Machine Learning, Android

Senior Software Engineer, Machine Learning, Android

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.

The Android Input Research (AIR) Text and Language Team is a part of the Gboard team, a team that builds and owns a product that servers billions of users. On this team, we conduct product-oriented research and development in the space of human-computer interactions by using technologies such as on-device ML models, large language models (LLMs), and GenAI agents, with the goal of enabling high-quality next-generation text-entry user experiences on mobile devices across the touch and voice modalities.

In this role, you will bring delightful and useful AI-powered features to mobile text entry. As an owner of the full life cycle of ML models, your role will involve opportunities and challenges in both natural-language data engineering and ML model development.

Android is Google's open-source mobile operating system powering more than 3 billion devices worldwide. Android is about bringing computing to everyone in the world. We believe computing is a super power for good, enabling access to information, economic opportunity, productivity, connectivity between friends and family and more. We think everyone in the world should have access to the best computing has to offer. We provide the platform for original equipment manufacturers (OEMs) and developers to build compelling computing devices (smartphones, tablets, TVs, wearables, etc) that run the best apps/services for everyone in the world.

The US base salary range for this full-time position is $166,000-$244,000 + 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.

Minimum Qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with ML/AI algorithms and tools, deep learning or natural language processing.
• Experience using Python libraries and frameworks.

Preferred Qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures/algorithms.
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.
• Experience with training and evaluation pipelines for various model sizes, specifically LLMs.
• Excellent communication skills for working with UX researchers and software engineers.

Responsibilities:

• Develop methods to compile, synthesize, and organize natural-language datasets that form the foundation of training and evaluating Gboard Machine Learning (ML) models.
• Establish and iteratively refine high-performance training and evaluation pipelines for a set of ML models ranging in size from small, fast on-device classifiers to powerful on-server Large Language Models (LLMs).
• Upgrade the team with the latest technologies in the area of LLMs and agentic AI and judiciously integrate them with prototyping and development efforts.
• Collaborate with frontend and backend software engineers in deploying these models in the Gboard app to support early prototyping and product feature launches.
• Work with UX/HCI researchers to develop experimental protocols for collecting high-quality online and offline user data to further augment the datasets for ML model training and evaluation.