Principal Engineer, Machine Learning Compute Services, Google Cloud

Note : By applying to this position you will have an opportunity to share your preferred working location from the following : New York, NY, USA;

Seattle, WA, USA; Sunnyvale, CA, USA

Minimum qualifications :

• 15 years of experience in software development, or 10 years with an advanced degree in Computer Science, Mathematics, Statistics, or Engineering.
• Experience in hardware and software design, data structures and algorithms, debugging, and with customer-facing products.

Preferred qualifications :

• Master's degree in a relevant field.
• Ability to work cross-functionally, partnering with groups such as Sales, Engineering, Product Management, Product Marketing, UX, and UI, brokering trade offs with stakeholders and understanding their needs.
• Outstanding narrative and storytelling skills that propel usage, adoption, and market momentum.

About The Job

As the Principal Engineer, you will be responsible for driving the Google Cloud Machine Learning Compute Services technical strategy, enabling highly scalable ML services powered by both GPUs and TPUs.

You'll provide technical leadership in this critical emerging AI / ML cloud use-case.

In this role, you will drive, execute, and deliver on the tech strategy for Cloud ML Compute’s overall ML services design for very large scale training and inference on GCP, as well as how these connect nicely to other GCP services such as GKE and Vertex AI.

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.

For US Candidates :

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

• Develop a strategic vision for the Google Cloud Platform organization to constantly innovate and implement novel solutions for next-generation ML and HPC infrastructure services.
• Design, build, and deploy solutions that leverage GPU, TPU, and highly-scalable hardware and software infrastructure to deliver compelling solutions for GPU, TPU, ML, and HPC workloads.
• Manage robust and scalable systems to get ahead of the exponential market demand.
• Manage exceptional scheduling and resource management initiatives to optimize GCP service offerings for batch workloads for the key technical computing and machine learning use-cases.
• Influence and establish engineering best practices through solid design decisions, processes, and tools.

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.

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