Graduate Software Engineer

2 weeks ago

London, United Kingdom Google Full time

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.
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 hardware/software co-design.
Experience with optimizing software for x86 or ARM CPUs, including familiarity with AVX or ARM NEON.
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; 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.
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.
Contribute to hardware/software co-design of future TPUs.
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