Software Engineer, PhD

5 Months ago • All levels • $141,000 PA - $202,000 PA
Software Development & Engineering

Job Description

Google Cloud is seeking a Software Engineer with a PhD to join their Machine Learning, Systems and Cloud AI (MSCA) team. The role involves designing, analyzing, and developing advanced ML systems across the stack, utilizing research expertise. Responsibilities include resolving complex technical issues, developing and reviewing code, and ensuring best practices. The successful candidate will collaborate on team projects, contributing to category-defining AI/ML solutions. This is a full-time position starting in 2025, offering the opportunity to work on impactful projects and contribute to products used by billions. The role requires strong programming skills (C, C++, Java, JavaScript, Python, or Golang) and experience with ML/AI systems in large-scale distributed environments. Experience with Unix/Linux, system architecture, or hardware/software integration is beneficial.
Good To Have:
  • Unix/Linux experience
  • Kernel development
  • Hardware/software integration
  • Performance optimization
  • Data analysis and visualization
Must Have:
  • PhD in CS or related field
  • Experience in ML/AI systems
  • Coding proficiency (C, C++, Java, Python, etc.)
  • Large-scale system design experience
  • Problem-solving and collaboration skills

Add these skills to join the top 1% applicants for this job

data-analytics
cpp
user-interface
networking
linux
unix
python
javascript
java
system-design
machine-learning


Minimum qualifications:

  • 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, JavaScript, Python, or Golang.

Preferred qualifications:

  • Experience in designing, developing, or applying ML/AI systems or applications in a large-scale distributed environment.
  • 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.

About the job

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 cutting-edge 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 !

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.

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 .

Responsibilities

  • Lead and collaborate on team projects to carry out design, analysis, and development of advanced Machine Learning (ML) systems 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).

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