Software Engineer III, On-Device Machine Learning
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.
Dialer Protection team's mission is to make every call valuable by leveraging AI.
One of the recently launched on-device LLM-powered features (e.g., scam detection on nano) is launched in Pixel feature drop 25'Q1.
As a Software Engineer, you will work on ML/Backend/Android, and we own the whole machine learning system that supports dialer AI features, including model training/fine-tuning, logging (in client), signal aggregation (pipelines), ML data curation (training/evaluation), experimentation, signal storage, model serving (on-device through AICore, server and pipeline generation asset) and testing, metrics and dashboard.
In this role, you will have opportunities to work in the following areas: on-device LLM deployment and serving (based on Gemini nano), next generation of on-device ML development, and scale product.
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 $141,000-$202,000 + 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
- Scope, design, develop, and launch innovative Calling AI features (based on Gemini) together with strong UX and Product teams.
- Work with client teams and other ML teams to deliver AI-powered features (like LLM) in Dialer.
- Explore or experiment on ML innovations to improve performance for protection.
- Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
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), ML infrastructure, 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.