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Software Engineer, Tensor Processing Units Compiler

England, United Kingdom (On-site)

Software Engineer, Tensor Processing Units Compiler

1 Month ago • 3-7 Years • Full Stack Development • Research & Development

About the job

8 skills required for this role

Test your skills to join the top 1% applicants for this job

tensorflow

cpp

algorithms

deep-learning

data-structures

pytorch

cuda

networking

Job Description

As a Software Engineer on the TPU Compiler team, 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. You'll be contributing to a compiler for a novel processor designed to accelerate machine learning workloads. You'll also be compiling high-performance implementations of operations at a distributed scale, working closely with users of TPUs to improve performance/efficiency, and hardware designers to co-design future processors. You'll be investigating high-level representations to effectively program large-scale, distributed, and heterogeneous systems.

Must have:

Bachelor's degree or equivalent practical experience
3 years of experience testing, maintaining, or launching software products
1 year of experience with software design and architecture
2 years of experience working with CUDA C++ application development
1 year of experience with Native Code, Just-In-Time (JIT), Cross, Source-to-Source or any other type of compilers
2 years of experience with data structures or algorithms
Experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning, or natural language processing

Good to have:

Master's degree or PhD in Computer Science or related technical fields
Experience with performance, large-scale systems data analysis, visualization tools, or debugging
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 in GPU integrating low-level CUDA work into higher-level frameworks (e.g., TF, JAX, PyTorch)

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Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
2 years of experience working with CUDA C++ application development and 1 year of experience with Native Code, Just-In-Time (JIT), Cross, Source-to-Source or any other type of compilers.
2 years of experience with data structures or algorithms, with experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning, or natural language processing.

Preferred qualifications:

Master's degree or PhD in Computer Science or related technical fields.
Experience with performance, large-scale systems data analysis, visualization tools, or debugging.
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 in GPU integrating low-level CUDA work into higher-level frameworks (e.g., TF, JAX, PyTorch).

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 (LLVM) as well as the Multi-Level Intermediate Representation (MLIR) 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

Contribute to a compiler for a novel processor designed to accelerate machine learning workloads. Compile high-performance implementations of operations at a distributed scale.
Work closely with users of TPUs to improve performance/efficiency and hardware designers to co-design future processors.
Investigate high-level representations to effectively program large-scale, distributed, and hetereogeneous systems.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.