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.
This role involves general software engineering of ML Fleet systems: writing code and tests, deploying services, setting up operational systems, triaging and fixing issues, etc.
In this role, you will build our ML Fleet Systems Software and to provide technical leadership to the team. You will involve deep technical engagement with design and code base, scoping and designing new features, overseeing production health, monitoring operational health and so forth.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.****Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design, develop, test, deploy, maintain, and enhance software features and components as part of a team.
- Analyze and resolve technical issues of moderate complexity, contributing to design choices and implementation details.
- Write high-quality, maintainable, and well-tested code, adhering to engineering best practices and participating actively in code reviews.
- Collaborate effectively with other engineers, and potentially with Product Managers and UX Designers, to achieve shared goals and deliver projects.
- Contribute to the operational health and reliability of ML Fleet systems, including debugging, bug fixing, monitoring, and continuous improvement efforts.
Qualifications
Minimum qualifications:
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience programming in Java, Python, Go or C++.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience with data structures and algorithms.
- Understanding of resource management systems (e.g., Kubernetes, Flex), cluster management, and scheduling algorithms.
- Familiarity with machine learning hardware accelerators (e.g., TPUs, GPUs) and their lifecycle management.
- Strong communication and teamwork skills. Ability to collaborate across boundaries.
- Strong problem solving, investigative and communication skills to work closely with peer engineering teams in the US.