Senior Software Engineer, Applied Machine Learning, AICore

Senior Software Engineer, Applied Machine Learning, AICore

Google campus, Mountain View, CA, USA

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

• 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 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.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.

Google's software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products handle information at massive scale and extend beyond web search. We need engineers who bring fresh ideas from information retrieval, distributed computing, large-scale system design, networking, data storage, security, AI, NLP, UI design, and mobile. A software engineer will work on a specific project critical to Google’s needs, with opportunities to switch teams and projects as the business evolves.

Our team is dedicated to crafting a GenAI capability by harnessing the potential of LLMs and other foundational AI models running directly on mobile devices. AICore was launched with the Pixel 8/9, Samsung S24, S25, Oppo, Xiaomi and other devices since 2023, gaining significant attention alongside the Gemini Nano announcement. Our mission is to innovate from within the Android platform and extend these benefits outward across the Android ecosystem.

In this role, you will deliver mobile experience changes by leveraging AI technology within the Android ecosystem. The Platforms and Devices team encompasses Google’s computing software platforms across environments (desktop, mobile, applications), as well as first-party devices and services. Teams research, design, and develop new technologies to make user interaction with computing faster and more seamless, building innovative experiences worldwide.

The US base salary range for this full-time position is $166,000-$244,000 plus bonus, equity, and benefits. Compensation details reflect the base salary only and do not include bonus, equity, or benefits. Learn more about benefits at Google.

• Collaborate with Google Deep Mind and Core Machine Learning to adapt and deploy the Gemini model for seamless integration into mobile user applications.
• Work on LLM fine-tuning, prompt optimization, and runtime optimization to improve user experiences for mobile end-users globally.
• Work closely with product teams to innovate and implement novel user experiences, leveraging techniques like Retrieval-Augmented Generation, traditional machine learning models, LoRAs, and targeted LLM fine-tuning.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity or expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, expecting parents, or criminal histories consistent with legal requirements, or any other basis protected by law.

See also Google's EEO Policy.

English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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