Senior Staff Engineer, JAX 3P, ML Accelerator Optimization

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience leading in machine learning design and optimizing machine learning infrastructure (model deployment and evaluation, data processing, debugging, fine-tuning, etc.).
• 3 years of experience with software design/architecture.
• Experience developing software applications using the C++ programming language.
• Experience with object-oriented programming, templates, and the Standard Template Library (STL).

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• Experience with hardware accelerators (TPUs, GPUs), including low-level optimization and performance tuning.
• Deep expertise in compiler design and optimization, including experience with XLA, LLVM, or similar compiler infrastructures.
• Strong understanding of machine learning frameworks (JAX, PyTorch or TensorFlow), including their internal architecture and performance characteristics.
• Demonstrated ability to identify and solve complex performance bottlenecks spanning multiple layers of the ML stack.

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

This role within the JAX 3P team involves developing innovative solutions at the intersection of ML frameworks (particularly JAX), compilers, and hardware accelerators (TPUs/GPUs). In close collaboration with other senior engineers, you will fundamentally rethink the assumptions underlying compilers, frameworks, and accelerators. This requires pushing the boundaries of performance and efficiency across the entire ML stack.

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 $248,000-$349,000 + 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.

• Provide leadership and development at the intersection of ML frameworks (JAX, PyTorch and TensorFlow), the XLA compiler, and hardware accelerators (TPUs/GPUs).
• Design and implement novel compiler optimizations and automatic kernel generation techniques, leveraging the unique capabilities of TPUs and GPUs.
• Investigate and prototype new programming models and hardware-software co-design strategies to unlock the full potential of emerging accelerator technologies.
• Collaborate closely with framework developers, compiler engineers, and hardware architects to influence the design of future ML systems.