Staff Software Engineer, Accelerator Platform Software

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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 Accelerator Platforms and Laboratory Team's mission is to empower Google's accelerator roadmap by engineering foundational hardware (Peripheral Component Interconnect Express, fabric, Input-Output Memory Management Unit) and low-level software (kernel, Firmware). We provide reliable, secure, and efficient accelerator-to-host connectivity to enable use cases. The team is also responsible for onboarding new types of domain-specific accelerators into Google data centers.

As a Staff Software Engineer on the accelerator platforms team, you will have influence beyond, handling complex issues in low-level software and hardware interaction.

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

• On-board emerging co-accelerators into Google's ML accelerator families to enable new use cases with improved performance and efficiency.
• Collaborate with internal teams to design and implement new features in system software, including firmware or daemons running on baseboard management controller/hosts and kernel drivers.
• Design and develop tests, tools, telemetry, and dashboards to generate insights to monitor and debug potential issues.
• Analyze, debug, and resolve complex system-level challenges related to kernel, virtualization (input-output memory management unit), and input/output (peripheral component interconnect express/compute express link) stacks.
• Provide technical leadership to help formulate and drive software development plans and identify dependencies in cross-functional teams.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience in testing, and launching software products.
• 5 years of experience in working with embedded operating systems.
• 3 years of experience with software design and architecture.
• Experience with C, C++, linux kernel, virtualization, and computer architecture.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, a technical related field, or equivalent practical experience
• 8 years of experience with data structures and algorithms.
• 3 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.
• Experience with one or more major kernel stack/subsystems: pcie, iommu, vfio/iommufd, dma-buf.
• Knowledge of any hardware-accelerated compute pipelines (GPUs, ML accelerators, DSPs) and its system integration (boot flow, firmware, telemetry).