Software Engineer, Infrastructure, PhD, Early Career, 2027 Start
Google· Internet & Cloud Services· Aug 24, 2026 · 2mo agoPosted 64 days ago
Sunnyvale, CA, USA · Atlanta, GA, USA · Austin, TX, USA · Kirkland, WA, USA · Los Angeles, CA, USA · Madison, WI, USA · Mountain View, CA, USA · New York, NY, USA · Raleigh, NC, USA · Durham, NC, USA · San Bruno, CA, USA · Seattle, WA, USA
In office
Full-time
Mid
$115K–$166K est.
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Job description
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.
As a PhD graduate, your research expertise is invaluable to us. Explore a variety of projects, collaborate with various teams, and contribute to products that are changing the world, across many product areas, including AI & Infrastructure , Cloud , YouTube , Search , Ads and more!
Our Engineering teams include thousands of PhDs who bring their deep knowledge and research experience to enhance our systems and products. As a Google PhD Software Engineer, you will work on critical projects, with many opportunities to learn and follow your interests. We expect our engineers to be creative and versatile, leading and identifying new problems to push the field and Google technology forward.
Google is one of the world’s leading suppliers and consumers of ML and AI technology, with decades of experience in designing, deploying, and using ML software and custom ML hardware infrastructure at massive scale.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
• Participate in or lead team projects to carry out design, analysis, and development of advanced systems across the stack, using your research expertise.
• Write documents that set new technical directions. Contribute to existing documentation or educational content, and adapt content based on product/program updates and user feedback.
• Study, diagnose and resolve complex technical issues by analyzing the sources of the issues and the impact on software, hardware, network, or service operations and quality.
• Develop code, review code developed by other developers, and provide feedback to ensure best practices (e.g., style guidelines, accuracy, testability, and efficiency).
• PhD degree in Computer Science, a related field, or equivalent practical experience.
• Experience coding in one of the following programming languages including but not limited to: C, C++, Python Java or Golang.
• Experience in one or more of the following: architecting or developing distributed systems, concurrency, multi-threading, or synchronization.
Minimum qualifications:
• PhD degree in Computer Science, a related field, or equivalent practical experience.
• Experience coding in one of the following programming languages including but not limited to: C, C++, Python Java or Golang.
• Experience in one or more of the following: architecting or developing distributed systems, concurrency, multi-threading, or synchronization.
Preferred qualifications:
• Research experience in algorithms, architecture, artificial intelligence, compilers, databases, data mining, distributed systems, machine learning, networking, or systems.
• Experience in designing and implementing a complex system, for production or experimental use.
• Experience with performance, reliability, systems data analysis, visualization tools, or debugging.
• Experience coding in Rust.
• Availability to start in a full-time role in 2027.
Application prep
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Keywords to mirror
aimlpythonjavagolangmachine learningrust
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