Senior Software Engineer, ML Infrastructure, Control Plane
Google· Internet & Cloud Services· Aug 4, 2026 · 3mo agoPosted 84 days ago
Sunnyvale, CA, USA
In office
Full-time
Senior
$150K–$200K est.
5+ years exp
Before you apply
Ghost Signal:
Open 84 days.
Job description
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.
Compute Infrastructure or cluster management system is the cornerstone of Google’s infrastructure—a cluster management system that has powered our global fleet for over 20 years. It is responsible for the optimal scheduling of virtually all ML and non-ML workloads across hundreds of data centers worldwide.
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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
• Design and deliver an orchestration layer for Google's AI workloads.
• Partner with executive technical leadership and cross-functional teams to turn business goals into concrete technical priorities and engineering roadmaps.
• Navigate open-ended architectural challenges and actively contribute to engineering efforts to drive key milestones.
• Influence technical direction and engineering practices across the broader Compute Infrastructure organization to drive consistency and best practices.
• Provide technical guidance and mentorship to a executive engineering team, helping them navigate open-ended architectural issues.
• Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages (e.g., Java, C++, Go, or Python).
• Experience in software architecture, system design, and distributed systems.
• Experience with Infrastructure as a Service (IaaS) cloud platforms (e.g., Google Cloud Platform).
Minimum qualifications:
• Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages (e.g., Java, C++, Go, or Python).
• Experience in software architecture, system design, and distributed systems.
• Experience with Infrastructure as a Service (IaaS) cloud platforms (e.g., Google Cloud Platform).
Preferred qualifications:
• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures/algorithms.
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.
• Experience in planning, building, and deploying machine learning infrastructure.
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Keywords to mirror
mlaijavagopythonmachine learning
- Platform
- Effort
- medium