Staff Software Engineer, Borglet ML, Offloads

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• Experience in cross-functional collaboration and working across boundaries.
• Experience working with Python, C++, or Go.

Preferred qualifications:

• Experience with system software, distributed systems, and complex multi-component software systems.
• Experience in developing and releasing system software products and C/C++ programming skills.
• Experience with Linux, GPU Drivers, and GPU Programming.
• Experience with the Linux kernel interface and containers.
• Understanding of key concepts of performance analysis and tuning.
• Ability to be reliable, and efficient.

About the job

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.

Our team builds a high performance, reliable and efficient Borglet for Google Cloud Offloads and Machine Learning (ML) use cases. We're part of the broader Borglet team, Google's node management agent. We’re a strong, systems-heavy team that works closely with Borg cluster management software, the kernel, with Hardware platforms and user applications.

The Borglet team runs as a set of smaller 10-15 person sub-teams, with Offloads and ML being two of them, executing on various projects in all major areas of infrastructure. Each team runs independently and is given a large amount of freedom, yet can still count on the support of the rest of the team. Our stack is mostly C++ with some Go used for cluster services.

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.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Serve as the technical lead of a team of engineers focussed on designing, implementing, and analyzing low-level computer systems and their interactions with the kernel and hardware.
• Collaborate with partner teams as well as users across Google (e.g., Borg team, ML teams, Hardware platform teams, SRE teams, Google Cloud, etc.).