Director, Engineering, ML Compiler

Minimum qualifications:

• Master's degree in Computer Science, Computer Engineering, a related field, or equivalent practical experience.
• 15 years of industry experience in compiler development, including machine learning optimization.
• 10 years of experience leading and growing technical teams.
• Experience with ML accelerators like TPUs or GPUs.

Preferred qualifications:

• Experience in computer architecture, high-performance computing.
• Experience building compilers for custom hardware architectures.
• In-depth knowledge of machine learning frameworks (e.g., Jax, PyTorch, TensorFlow).
• Outstanding communication skills tailored to both technical and non-technical audiences.
• Contributions to open-source compiler projects.

About the job

Google is a leading ML/AI company. Google’s Core ML team aims to build state-of-the-art AI platforms, services, and tools behind Google’s AI research and AI-powered products. We are owners of the Google AI framework (e.g., TensorFlow, JAX), AI performance and efficiency, AI training and inference platforms, AI compilers (e.g. XLA), AI software/hardware co-design (e.g. TPU), and AI developer experience (e.g., Model Hub, Eval Hub). We are the driver to launch Large Models (like Gemini) from research to production and enable all Google products to adopt LMs to improve end-user experiences. The CoreML team is responsible for planning and optimizing ML capacity for all Google products and driving performance and efficiency work to maximize ROI for our AI investments. We look across Google’s AI efforts to build central solutions, break down technical barriers, and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

We are seeking an exceptional and experienced leader to build and direct our ML Compiler team. This pivotal role presents the unique opportunity to shape Google's hardware strategy by orchestrating the development of cutting-edge machine learning compilers. You'll work at the intersection of research, product development, hardware engineering, and core machine learning teams to seamlessly execute the ML Compiler roadmap.

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

• Define the long-term strategic vision for our ML compiler technology and roadmap. Establish technical direction, goals, and development priorities.
• Recruit, mentor, and develop a highly skilled team of compiler engineers focused on machine learning optimization. Create a collaborative and high-achieving work environment.
• Forge strong partnerships with research, product, hardware, and core ML teams. Drive alignment and effective collaboration to ensure optimal compiler solutions for Google's custom TPU and GPU strategies.
• Apply your deep expertise in compilers and machine learning to optimize system performance, reduce software overheads, and seamlessly support new hardware. Advocate innovation and the application of new technologies.
• Cultivate a deep understanding of customer needs, driving a relentless focus on enabling their success through compiler capabilities.