Senior Software Engineer - AI and Infrastructure

Senior Software Engineer, AI and Infrastructure, CMCS

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with distributed computing, infrastructure as code, infrastructure as a service, and system design.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 5 years of experience with data structures and algorithms.
• 3 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture
• Experience as a software engineer.
• Experience in any one of GCP or other cloud providers, or other data center management stack.
• Knowledge in three or more of the following areas: APIs and services, distributed systems, tools, testing infrastructure, and monitoring infrastructure.

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.

CMCS (Cloud ML Compute Services) team defines and drives the overall Cloud ML Compute IaaS and IaaS+ product offering and technical strategy.

In this role, you will enable the customers with the best Machine Learning (ML) and High Performance Computing (HPC) platform in the world for top talent powered by TPUs, GPUs, CPUs and all ML frameworks (Tensorflow, PyTorch and JAX).

In this role, you will enable the customers with the best Machine Learning (ML) and High Performance Computing (HPC) platform in the world for top talent powered by TPUs, GPUs, CPUs and all ML frameworks (Tensorflow, PyTorch and JAX).

Responsibilities

• Own the design, development, and deployment of scalable software components that enable the deployment of AI and ML infrastructure.
• Troubleshoot complex distributed system issues across the stack (hardware, kernel, network); build the automation, tooling, and telemetry needed to turn operational findings into permanent software fixes and improved SLOs. 
• Collaborate closely with Hardware, Networking, Storage, CE, Product and other partner teams to define requirements and deliver high-quality solutions.
• Lead code reviews, drive engineering best practices (testing, release safety), and mentor junior engineers to help grow the technical capability of the team.
• Contribute to the team's technical roadmap by identifying infrastructure gaps and proposing architectural improvements to support future growth.

Experience Level

Senior Level