Software Engineer, ML Infrastructure, Chrome
2 days ago
- Bachelor's degree or equivalent practical experience.
- 2 years of software development experience in one or more general-purpose programming languages (e.g., C++, Java, Python, Go).
- Experience with the software development life-cycle, including testing, deployment, and maintenance.
- Experience contributing to the design of software systems or features, along with working on codebases.
- Master's degree or PhD in Computer Science or related technical fields.
- Experience contributing to code bases like Chromium.
- Experience with machine learning concepts, tools, and frameworks (e.g., TensorFlow, TFLite).
- Experience with ML infrastructure, such as model serving platforms, data pipelines, or ML operations.
- Experience in ML performance, large-scale systems data analysis, ML debugging, LLMs, or specialized areas within ML.
- Knowledge of on-device ML deployment and optimization techniques.
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.
Chrome browser's strategy is to become more smarter, personalized, and proactive. That is where our team comes in. The Chrome Intelligence Infrastructure team's goal is to build both GenerativeAI and non-GenerativeAI Machine Learning infrastructure and capabilities to accomplish Chrome's strategy. We build and support the infrastructure and services that enable Chrome feature teams to quickly incorporate intelligence into their solutions, impacting billions of users. This includes on-device ML model delivery and inference, server-side metadata and GenAI services, and data pipelines. We are working on the latest technologies to deliver agentic solutions to users.
Chrome is dedicated to building a better, more open web. We're focused on making a better browser (on both desktop and mobile) to help users take advantage of all the web has to offer in a safe and secure way.Chrome is available across all major platforms — iOS, Android, Windows, Mac, Linux and Chrome OS. We also built Chrome as an open source project so the entire web ecosystem could benefit from the latest innovations in speed, simplicity and security.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:
- Build and maintain scalable and reliable ML infrastructure to support on-device and server-side intelligence features in Chrome, contributing to design discussions with guidance from executive engineers.
- Develop and optimize systems for model management, serving, and execution, potentially including components within Google3 (e.g., using Go, C++, Java) and Chromium (C++).
- Collaborate with Chrome feature teams to understand requirements and integrate ML solutions into the Chrome browser.
- Contribute to the design and implement components of larger projects, potentially owning smaller end-to-end tasks under supervision.
- Enhance the performance, efficiency, and monitoring of our ML systems and services, while contributing to code health, system maintainability, and documentation.
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