Software Engineer lll, Cloud Machine Learning Compute Services
Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Oct 28, 2026. Google scores B on the Alion truth index.
About the job
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 is a high-impact opportunity for a Software Engineer to build mission-critical distributed systems and control planes that power Google's largest AI supercomputers. You will take end-to-end ownership of features and components that bridge utility grid constraints, data center power infrastructure, and large-scale Cloud Tensor Processing Units (TPUs) clusters. By delivering resilient automation, high-recall alerting, and intelligent power actuation, your work directly enables Google's strategic AI customers to scale frontier model training and inference safely and efficiently within data center megawatt limits.
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
- Build and maintain the software systems and control planes that run Google's Cloud TPU infrastructure.
- Own end-to-end features across the TPU software stack, which may include cluster and fleet management, power and resource orchestration, host and runtime software, hardware qualification, or fleet health and observability.
- Write production code, build automated validation pipelines, and improve telemetry and tooling to keep large-scale TPU clusters reliable and efficient for AI training and inference workloads.
- Design, implement, and test software components, debug complex issues across distributed systems and hardware interfaces, and take features from initial design to production roll-out.
- Work closely with partner engineering teams across Google Cloud and data center infrastructure to understand customer and operational requirements.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 2 years of experience with AI Platforms.
- 1 year of experience developing/launching products/technologies within software as a service or a related area.
- Experience developing/launching products/technologies within Cloud Infrastructure.
Preferred qualifications:
- Bachelor's, Master's, or PhD degree in Computer Science, a related technical field, or equivalent practical experience.
- 2 years of experience in software development (or 1 year with a relevant advanced degree), building and testing reliable backend or distributed systems in C++, Go, Python, or Java.
- Experience designing and executing testing strategies beyond unit tests and maintaining production service health.
- Experience with Machine Learning Infrastructure.
- Strong foundation in software engineering, distributed systems, and production reliability, with a demonstrated ability to independently deliver end-to-end features and components in a collaborative, fast-paced environment.