Principal Engineer, GPUs, Core ML, Borg, Spatial Flex

Minimum qualifications:

• Bachelor's degree in Computer Science, a similar field, or equivalent practical experience
• 15 years of experience in GPU performance related work
• 15 years of experience working with GPU Inference optimization

Preferred qualifications:

• 18 years of professional experience in GPU performance related work at all levels of the stack
• Deep understanding of modern GPU architectures memory hierarchies, and performance bottlenecks.
• Ability to develop and utilize sophisticated performance models and benchmarks to guide optimization efforts and hardware roadmap decisions
• Excellent communication and people skills, with the ability to effectively collaborate with customers and internal teams
• Expertise in tailoring algorithms and ML models to exploit GPU strengths and minimize weaknesses

About the job

Core ML is searching for a highly skilled and motivated Principal Engineer to play a leadership role in evaluating a collection of forthcoming hardware technologies for optimizing our offerings in this space. You will work on advanced evaluation of GPU offerings and work closely with the internal TPU offerings to properly position and advocate for both cloud and internal customer GPU use-cases. In this role, you will also directly contribute across Cloud and other Product Areas in creating the right infrastructure to access our ML Systems.

This team is tasked with achieving state-of-the-art performance of many key models on GPU when compared to industry or internal TPUs, by performing classic performance work or building infrastructure to automate much of it, including the fungibility of models between hardware platforms.

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 $294,000-$414,000 + 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.

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

• Provide engineering leadership and strategic product vision in this critical emerging Cloud use-cases as well as important internal use cases. 
• Lead efforts to optimize machine learning models for speed, memory efficiency, and accuracy through experimentation with different architectures, hyperparameters, and optimization techniques.
• Translate customer requirements into technical solutions by working closely with them to understand their needs. This includes presenting technical findings and recommendations.
• Guide and inspire junior engineers by leading by example, sharing your expertise, and providing guidance on best practices.
• Identify bottlenecks and areas for improvement by developing and utilizing performance analysis tools.