Senior Staff Software Engineer, AI/ML, Google Cloud
First seen by Alion on Aug 19, 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.
The Cloud GPU team is central to AI innovation, dedicated to building and maintaining an industry-leading GPU fleet and AI Platform. Our core mission is to empower Google Cloud's most sophisticated training and inference customers by providing unparalleled computational resources. We're responsible for the lifecycle of GPU offerings from the initial launch of new GPU families to ensuring their optimal reliability and operational excellence for cutting-edge AI workloads.
Our team thrives at the intersection of hardware, software, data science and applied AI, pushing the boundaries of what's possible in accelerated computing. We collaborate closely with internal and external partners to deliver the foundational infrastructure that fuels advancements in AI across industries.
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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Execute technical roadmaps for the GPU ecosystem, anticipating market shifts to keep Google Cloud at the forefront of AI infrastructure.
- Collaborate with engineering teams to integrate new GPU architectures into Google Compute Engine (GCE) for rapid workload availability.
- Oversee the lifecycle of accelerator solutions, guaranteeing consistent performance and stability for user applications.
- Serve as a technical advocate during critical issues, collaborating directly with customers to resolve challenges and translating their feedback into platform enhancements.
- Design robust software solutions meeting the massive scalability and performance requirements of Google Cloud’s global network.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 7 years of experience leading technical project strategy, ML design, and optimizing industry ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience with design and architecture; and testing/launching software products.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.