Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- Candidates will typically have 5 years of experience working with Compute Unified Device Architecture (CUDA) C++ application development.
- Typically 3 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning, or natural language processing.
- Typically have 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- Typically have 2 years of experience with data structures or algorithms.
- Typically 2 years of experience with Native Code, Just-In-Time (JIT), Cross, Source-to-Source, or any other type of compilers.
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Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience with debugging correctness and performance issues at all levels of the stack.
- Experience with optimizations in mid-level and low-level architecture.
- Experience with hardware/software co-design.
- Experience with optimizing software for x86 or ARM CPUs, including familiarity with AVX or ARM NEON.
About the job
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.
Our team builds the compiler which enables Tensor Processing Units (TPUs), Google's in-house custom designed processor, to accelerate machine learning and other scientific computing workloads for both internal Google customers and external Cloud customers. The team offers opportunities up and down the compiler stack, working on Low Level Virtual Machine as well as the Multi-Level Intermediate Representation middle-end.
In this role, you'll be working on the MLIR/LLVM based TPU compiler for TPUs. You will support new workloads, optimize for new models and new characteristics, as well as support new TPU hardware across multiple generations.
Google Cloud accelerates organizations' ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology - all on the cleanest cloud in the industry. 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
- Evaluate and improve the performance of ML models end-to-end, and identify key performance bottlenecks both on the TPU device and the host.
- Develop novel compiler optimizations that provide performance wins to end users.
- Implement compiler support for new TPU hardware features.
- Contribute to hardware/software co-design of future TPUs.