Software Engineer, PhD, Early Career, Networking, 2026 Start
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Software Engineer, PhD, Early Career, Networking, 2026 Start
Location
Bengaluru, Karnataka, India
Experience
Entry
Posted
Jul 18, 2026
Apply by
August 17, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
Minimum qualifications: PhD degree in Computer Science, Electrical Engineering, or a related technical field. Experience coding in one of the following programming languages including but not limited to: C, C++, Java or Golang. Experience in software development, with a focus on areas such as large-scale distributed systems and networking. Experience in algorithms, complexity analysis, and system design. Preferred qualifications: Experience working with SmartNIC technologies. Ability to act as a generalist software engineer blending technical execution with program management and process optimization. Ability to lead multiple workstreams with attention to detail. Ability to write and review code, ensuring adherence to best practices in style, accuracy, testability, and efficiency. Ability to investigate, diagnose, and resolve technical issues by analyzing root causes and impact.
About the job 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. We seek innovative engineers with various expertise, including information retrieval, distributed computing, large-scale system design, networking, data storage, security and AI/ML. Within Google Cloud, the AI and Infrastructure(AI2) organization is at the forefront of creating groundbreaking AI/ML capabilities. We are responsible for designing and managing the software, hardware, and Machine Learning (ML) systems infrastructure that power essential Google services such as search and YouTube, as well as Google Cloud products. As a PhD Software Engineer within AI2, your specialized research expertise will be instrumental in solving complex, real world problems on an unprecedented scale. You will engage in innovative projects spanning areas like AI/ML, networking, data storage, security, and distributed systems.
Responsibilities Develop kernel drivers for the various Infrastructure Processing Units (IPUs)/Network Interface Cards (NICs) in our portfolio, and ensuring that end-to-end systems built with these devices achieve the scale, reliability, performance expected of networking, and that such systems interact well within the Google Cloud ecosystem.
Key Responsibilities
- Develop kernel drivers for Infrastructure Processing Units (IPUs) and Network Interface Cards (NICs).
- Ensure end-to-end systems built with these devices achieve scale, reliability, and performance.
- Ensure systems interact well within the Google Cloud ecosystem.
- Write and review code to ensure adherence to best practices in style, accuracy, testability, and efficiency.
- Investigate, diagnose, and resolve technical issues by analyzing root causes and impact.
Requirements
- PhD degree in Computer Science
- Electrical Engineering
- or a related technical field
Skills Required
CC++JavaGolangSoftware developmentLarge-scale distributed systemsNetworkingAlgorithmsComplexity analysisSystem designLeadershipAttention to detailProblem solvingVersatilitySmartNIC technologiesGeneralist mindsetProgram managementProcess optimization
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