Senior ML Compiler Engineer, GPU
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Minimum qualifications:
- Bachelor's degree in Computer Science, Information Technology, Engineering, a related technical field, or equivalent practical experience.
- 5 years of experience in software development.
- Experience in programming languages such as C++.
Preferred qualifications:
- Experience in contributing to an open-source project.
- Experience working in HPC/GPU workloads.
- Experience with compilers, compiler construction, and Low-Level Virtual Machine (LLVM).
- Experience with ML frameworks (e.g., PyTorch, JAX, TensorFlow).
- Experience in computer science, with strong expertise in data structures, algorithms, and software design.
- Ability to communicate and navigate within rapidly changing environments.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.
Accelerated Linear Algebra (XLA) is Google's open-source machine-learning compiler which applies techniques to accelerate ML workloads. Our problem-space is the intersection of compilers, machine-learning and high-performance GPU development.You will help XLA accelerate machine learning applications, like Large Language Models and Generative AI, to run at their fullest potential on GPUs.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s 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.
Responsibilities
- Partner with users of XLA on GPU as part of a high-investment and high-priority program to make ML on GPU successful at Google.
- Design and launch new GPU optimizations and features, including performance and correctness testing.
- Enhance the GPU compiler software stack so that it performs faster and more efficiently on ML workloads.
- Foster deep collaboration between the GPU Software team, customer teams, Google research and the open-source community.
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