Senior Software Engineer, Applied Machine Learning, AICore

Google•Apply•Published 12 hours ago•First seen 12 hours ago

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.

Our team is dedicated to crafting a GenAI capability by fully 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 and Oppo, Xiaomi etc devices since 2023 and gaining significant attention alongside the Gemini Nano announcement, our mission is to innovate from within the Android platform and extend these benefits outward, influencing mobile experiences everywhere. Beyond Pixel, we are working with Original Equipment Manufacturers (OEMs) across the Android ecosystem.

In this role, you will be delivering mobile experience changes by leveraging AI technology within the Android ecosystem.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around 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.

Responsibilities

Collaborate directly with Google DeepMind and Core Machine Learning to adapt and deploy the Gemini model for seamless integration into mobile user applications.
Work on Large Language Model (LLM) fine-tuning, prompt optimization, runtime optimization to improve user experiences for mobile end-users in the global market.
Work closely with product teams to innovate and implement novel user experiences, leveraging techniques like Retrieval-Augmented Generation (RAG), traditional machine learning models, LoRAs, and targeted LLM fine-tuning.

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 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).

Preferred qualifications:

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.
Experience developing accessible technologies.