Machine Learning Compiler Engineer, Silicon

As a software engineer at Google, you will be developing next-generation technologies that revolutionize how billions of users connect, explore, and interact with information and each other. The products you work on will need to handle information at massive scale and go beyond conventional web search. We are seeking individuals who can bring innovative ideas from a wide range of areas including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile technologies. The scope of work covers various domains and is continuously expanding. Your role as a software engineer will involve working on crucial projects that cater to Google's requirements, with opportunities to transition between teams and projects as both you and the dynamic business environment evolve. Versatility, leadership qualities, and a proactive approach to tackling new challenges across the full technology stack are essential traits we look for in our engineers. Google's ultimate mission is to organize the world's information and make it universally accessible and beneficial. Our team leverages the best of Google AI, software, and hardware to create solutions that significantly enhance user experiences. Key Responsibilities: - Develop compilers and tools that facilitate the mapping of machine learning models, focusing on computing use cases, to the hardware Infrastructure Support Agreement (ISA). - Assess different parallelization strategies considering performance, power, energy, and memory consumption trade-offs. - Collaborate closely with machine learning researchers to enhance the domain-specific compiler. - Work in conjunction with hardware engineers to drive the evolution of future accelerators. Minimum Qualifications: - Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. - 2 years of experience in C++ development. - Proficiency in data structures and algorithms. Preferred Qualifications: - Master's degree in Computer Science, a related technical field, or equivalent practical experience. - Experience with compilers and performance optimizations. - Familiarity with Low-Level Virtual Machines (LLVM).,