Software Engineer, PhD, Campus, Machine Learning, Systems and Cloud AI, GPU Performance, 2025 Start

About the position

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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 part of MSCA, (Machine Learning, Systems and Cloud AI), you will have the opportunity to be a part of an organization that delivers category-defining AI/ML solutions and capabilities, developed and powered by Google Services, Frameworks and Infrastructure, supporting customers around the world. Google's 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 a massive scale. You'll be at the forefront of innovation, developing solutions AI, machine Learning, distributed computing, and more. As a new PhD graduate, your research expertise is invaluable to us. Join the ML Systems and Cloud AI organization and apply your knowledge to real-world problems, that scale to billions of users. Explore a variety of projects, collaborate with teams, and contribute to products that are changing the world. 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 a specific project critical to MSCA's needs with opportunities to switch teams that follow your interests. We need our engineers to be creative and versatile, display leadership qualities and be enthusiastic to take on new problems as we continue to push 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 Machine learning (ML) software and custom ML hardware infrastructure at massive scale. Learn more about us here! While known for pioneering work with TPUs, GPUs are an equally vital and rapidly expanding frontier within Google's machine learning infrastructure. GPUs are indispensable to Google's diverse and ever-evolving landscape for strategic, pragmatic, and performance-driven reasons, ensuring top performance for our ML models, adapting to diverse ML workloads, achieving exceptional results, and influencing next-gen GPU architectures. This is your opportunity to move beyond incremental improvements and architect truly transformative solutions, shaping the future of AI and accelerated computing for Google and the world. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• 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.
• Develop code and review code developed by other developers, and provide feedback to ensure best practices (e.g., style guidelines, accuracy, testability, and efficiency).

Requirements

• PhD degree in Computer Science, or a related technical field, or equivalent practical experience.
• Experience coding in one of the following programming languages including but not limited to: C, C++, Java or Python.

Nice-to-haves

• Experience with any of the following: Compilers, GPU Programming, Machine Learning Architecture, Performance Optimization, Benchmarking, Runtimes, or Machine Learning Algorithms.
• Experience with performance, reliability, systems data analysis, visualization tools, architecture, compilers, database, data mining, 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.
• Ability to start full-time role in 2025.

Benefits

• 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.
• Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.