Software Engineer, PhD, Early Career

About the Role: Software Engineer, PhD, Early Career at Google

As a Software Engineer, PhD, Early Career at Google, you will be instrumental in developing next-generation technologies that shape how billions of users interact with information and each other. This role focuses on projects critical to Google Cloud's evolving needs, offering flexibility to move between teams and initiatives as you grow. You'll be empowered to act as an owner, proactively identifying customer needs, driving innovation, and tackling challenges across the full technology stack.

Within the Machine Learning, Systems, and Cloud AI (MSCA) organization, you'll contribute to category-defining AI/ML capabilities built on Google’s advanced frameworks and infrastructure. Your research expertise will address real-world problems at a massive scale, collaborating on innovative projects in AI, ML, and distributed systems that power services like Search and YouTube, and Google Cloud products.

Google prioritizes security, efficiency, and reliability, from developing TPUs to operating one of the world's largest networks, shaping the future of hyperscale computing. The AI and Infrastructure team delivers unparalleled scale, efficiency, reliability, and velocity to Google customers, including Googlers, Google Cloud clients, and billions of users worldwide.

You will be a driving force behind Google's groundbreaking innovations, empowering the development of cutting-edge AI models, delivering immense computing power, and providing essential platforms for future developers. Our teams are at the forefront of shaping world-leading hyperscale computing, with key contributions to TPUs, Vertex AI for Google Cloud, Google Global Networking, data center operations, and systems research.

Minimum Qualifications

• PhD degree in Computer Science, a related technical field, or equivalent practical experience.
• Experience coding in one of the following programming languages: C, C++, Java, or Python.
• Experience in one or more of the following: architecting or developing distributed systems, concurrency, multi-threading, or synchronization.

Preferred Qualifications

• Experience with performance, reliability, systems data analysis, visualization tools, or debugging.
• Experience in code and system health, diagnosis and resolution, and software test engineering.
• Research experience in algorithms, architecture, artificial intelligence, compilers, database, data mining, distributed systems, machine learning, networking, or systems.
• Experience with Unix/Linux, Kernel development, microcontrollers, SoC, device drivers, hardware, power management, ARM processors, performance optimization, file systems, bootloading, firmware, x86 assembly, system BIOS, or hardware/software integration.

Responsibilities

• Write product or system development code.
• Participate in, or lead design reviews with peers and stakeholders to decide on available technologies.
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Lead and collaborate on team projects to carry out design, analysis, and development across the stack using your research expertise.
• Study, diagnose, and resolve complex technical modeling and systems issues by analyzing the sources of the issues and the impact on quality.

Key skills/competency

• Distributed Systems
• Machine Learning
• Artificial Intelligence
• System Design
• Data Structures
• Algorithms
• Software Development
• Python/Java/C++
• Cloud Computing
• Performance Optimization