PhD Software Engineer

1 Month ago • All levels • Artificial Intelligence • $141,000 PA - $202,000 PA

Job Summary

Job Description

Google is seeking a PhD Software Engineer to join their Machine Learning, Systems, and Cloud AI (MSCA) organization. This role involves leading and collaborating on projects, designing, analyzing, and developing advanced systems. Responsibilities include resolving complex technical issues, developing and reviewing code, and ensuring best practices. The ideal candidate will have a PhD in Computer Science or a related field, experience in distributed systems and coding languages (C, C++, Java, JavaScript, Python, or Golang), and a strong research background in areas like AI, machine learning, or distributed systems. The position offers the chance to work on cutting-edge technology impacting billions of users and collaborate with diverse teams.
Must have:
  • PhD in Computer Science or related field
  • Experience in distributed systems
  • Proficiency in C, C++, Java, JavaScript, Python, or Golang
  • Strong research background in AI/ML
Good to have:
  • Experience with performance, reliability, data analysis, visualization
  • Experience architecting or developing distributed systems
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


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.
  • 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.
  • Research experience in algorithms, architecture, artificial intelligence, compilers, database, data mining, distributed systems, machine learning, networking, or systems.
  • 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 diverse 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 !

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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 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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