Principal Engineer, Google Compute Engine - Google

Seattle, WA

About the Job

Minimum qualifications:

Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent practical experience
15 years of experience in software development, specifically in software design, data structures and algorithms
Experience working with private and public cloud design considerations and challenges in the areas of operating systems, virtualization, multi-tenancy, fault-isolation, distributed systems, networking, and security with technical paper publications and conference engagements

Preferred qualifications:

Experience successfully building software and large-scale distributed systems
Demonstrated ability to work cross-functionally, partnering with groups such as Engineering, Product Management, Finance, Account Management, Operations, Product Marketing, UX and UI, brokering trade offs with stakeholders, understanding their needs, and driving consensus
Outstanding narrative and storytelling abilities that propel usage, adoption, and market momentum
Strong organization and prioritization skills along with outstanding written and verbal communication skills
Strong analytical and debugging skills working on customer-facing products
Proven track record of driving execution, proactively managing risks, and delivering against timelines

About the job

Google Compute Engine (GCE) is a cloud computing platform that empowers its users with a comprehensive suite of VM and Baremetal instances for General-Purpose Compute, Compute-Optimized, Memory-Optimized, Storage-Optimized, and GPU/TPU-Accelerated Workloads. GCE is one of Google Cloud Platform's (GCP) core services, and it is used by businesses of all sizes, from startups to enterprises running AI/ML, Cloud Native, and Mission Critical Enterprise services.

As a Principal Engineer in Google Compute Engine (GCE), you'll be at the forefront of cloud innovation, ensuring our specialized instance offerings meet the evolving needs of both enterprise and AI/ML customers. Our workload-optimized portfolio also includes memory and storage-optimized instances built on the foundation of Titanium. Storage-optimized instances are ideal for data-intensive applications like high-performance databases (e.g., SAP HANA), data warehousing, and large-scale media processing, where rapid access to vast datasets is essential. Memory-optimized instances exceed at running in-memory databases (e.g. Redis) and real-time analytics platforms (e.g. Apache Spark). You'll also take on the challenge of providing low-latency, high-throughput storage solutions essential for the exponential growth of AI/ML clusters. This includes optimizing for applications that require rapid access to training data, checkpointing, and model serving, where local SSDs and storage-optimized VMs are critical for achieving optimal performance. You will drive technical innovation to push the boundaries of performance, reliability, and cost-efficiency across all these workloads, ensuring our customers have a seamless and exceptional experience. This is an opportunity to shape the future of cloud computing by directly impacting the core compute offerings of Google Cloud Platform.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $278,000-$399,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

Establish industry-leading workload-optimized portfolio by defining GCE instances that meet the stringent resource, reliability, and performance demands of large-scale AI/ML clusters and mission-critical applications.
Lead the design, development, and optimization of GCE instances tailored to the unique performance and reliability needs of diverse workloads. This includes collaborating with internal teams and hardware vendors to ensure optimal performance and efficiency.
Build strong relationships with enterprise and AI/ML customers to understand their current and future requirements for GCE instance.
Provide technical guidance and mentorship to tech leads responsible for various aspects of the specialized GCE instance portfolio.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Source : Google