Compute Library Engineer

4 weeks ago

Cambridge, United Kingdom Neubla Full time
Compute Library Engineer in Cambridge, UK

About NeublanAs pioneers of innovative neural computing, Neubla is transforming the future of computing by bringing the enormous potential of neural computing to the highest performance in most data-intensive applications. Neubla is made up of people with expertise and lots of experience in many different fields such as AI, semiconductor design, and compilers. At Neubla, you can work in a rapidly changing environment where your new ideas will become innovative products, services, and customer experiences, working with talented colleagues. Neubla offers a competitive package with benefits, including health insurance, a pension scheme, employee wellness support, and a variety of snacks in the office

SummarynAs a Compute Library (CL) Engineer at Neubla, you will play a crucial role in the dynamic team responsible for crafting and optimizing the Compute Library tailored specifically for our designated hardware platform. Your contributions will be instrumental in advancing the capabilities and performance of our cutting-edge technology.

Job DescriptionnDevelop high-performance kernels for machine learning operators on NPU architecturesnOptimize existing kernels to ensure maximum efficiency and performancenCollaboratae with the hardware and software teams to integrate kernels into the NPU frameworknConduct thorough testing and debugging of kernels to ensure reliability and functionalitynUtilize hardware features of GPU and accelerators specialized for AI applications, including convolutions, matrix multiplication units and high-bandwidth interconnectionsnDocument and maintain clear, concise, and comprehensive code and design documentation

QualificationsnMasters, PhD, or equivalent experience in Computer Engineering, Electrical Engineering, or related fieldnMinimum of 5 years of experience in kernel development for NPUs, GPUs, or similar hardware accelerators from 3 ~ 5 years (ML, linear algebra)nProficiency in CUDA, OpenCL, or similar parallel programming languagesnExperience in SIMD/vector processing experience(RISC-V Vector)nStrong software development skills using standard development tools (e.g., Git, Jira, etc.)nBasic understanding of machine learning frameworks (TensorFlow, PyTorch, etc.)nExcellent problem-solving skills with a logical and analytical mindsetnStrong communication and interpersonal skills to collaborate effectively within a team environmentnAbility to work independently, manage multiple tasks, and thrive in a fast-paced, dynamic work environment

Preferred QualificationsnExperience in optimizing kernels for power efficiency and low-latency applicationsnFamiliarity with hardware architecture and system-level understanding of NPUs or GPUsnKnowledge of performance profiling tools and methodologiesnContributions to projects related to parallel computing or machine learning

The ProcessnApplication review > 1st Interview > 2nd Interview (technical) > 3rd Interview

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