Director, Engineering, TPU Performance
- linkCopy link
- emailEmail a friend
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:
- Master's degree or PhD in Computer Science or a related field.
- Excellent communication skills, with the ability to influence and align senior leaders and stakeholders across the company.
- Strong business acumen and the ability to make strategic decisions that balance technical trade-offs with business needs.
- Proven track record of delivering significant performance and efficiency improvements in large-scale systems.
- Deep expertise in computer architecture, compilers, and performance analysis tools.
About the job
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.
Responsibilities
- Lead and grow a large, globally distributed team of software engineers and technical leaders, fostering a culture of innovation, collaboration, and inclusivity.
- Develop and execute a long-term technical vision and strategy for ML performance and efficiency, aligning with Google's broader AI/ML and business objectives.
- Drive the successful delivery of large-scale, business-critical projects, including the optimization of flagship models like Gemini and the continuous improvement of fleet-wide TPU utilization.
- Build and maintain strong relationships with senior leadership and key stakeholders across product areas like GDM/Gemini, Search, YouTube, Ads, and Cloud/Vertex.
- Provide technical guidance and oversight on complex performance challenges, from low-level hardware optimizations to high-level algorithmic and system-wide improvements.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.