Director, Engineering, TPU Performance

Director, Engineering, TPU Performance

Google's future is AI, and our team is responsible for powering the transformation. Core ML supports the AI infrastructure used by every part of Google, from DeepMind to Search, YouTube, Ads, and more. We also enable Google Cloud users and Open Source communities to join this revolution, creating the tools to access and use the world's most powerful AI supercomputers (Tensor Processing Units and the latest GPUs).

As the Engineering Director for the TPU Performance team, you will lead an organization dedicated to maximizing the efficiency and performance of Google's machine learning workloads. You will be at the forefront of AI / ML innovation, driving the strategy and execution for optimizing large-scale model training and serving on our cutting-edge accelerator hardware.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud's Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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.

Minimum Qualifications :

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 15 years of professional experience in software development, with a focus on performance analysis, distributed systems, or a related area.
• 5 years of experience in a leadership role, managing engineering teams and driving cross-functional projects.
• Experience with machine learning frameworks (e.g., JAX, PyTorch, TensorFlow).
• Experience with machine learning model architectures, algorithmic performance, large-scale pretraining, low-latency serving, etc.
• Experience with hardware accelerators (e.g., TPUs, GPUs) and their programming models.

Preferred Qualifications :

Responsibilities :

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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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