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Job Description About the Company : Our client is a company building the world's highest-performance pure digital AI inference chip. Responsibilities : Advance the state of the art in compiler and runtime technology for delivering high-performance acceleration of AI workloads across a variety of neural network architectures. Research and design new software and hardware AI solutions, involving simulators, optimizing compilers, code generators, and runtime execution frameworks for deep learning accelerators. Evaluate various trade-offs of different parallelization strategies such as performance, power, energy, and memory consumption. Enhance AI software tools to support the latest DNNs emerging from the research community and industry. Keep up with the fast-paced development happening in industry and academia to continuously improve our products. Work closely with other software and hardware engineers to develop the next generation of deep learning software. Collaborate with architects and hardware engineers to co-design future accelerators. Preferred Skills & Experience : 10+ years of experience developing software for highly parallel architectures. Experience with optimizing algorithms for hardware acceleration, machine learning accelerators, spatial architectures, or GPUs. Strong problem-solving skills and the ability to resolve complex issues with ambiguity. Understanding of Deep Learning fundamentals. Strong development skills in C / C++, Python. Excellent soft skills: ability to work effectively in a team and influence cross-functional teams without direct authority. Degree in Computer Science, Engineering, or related field; MS or PhD preferred. Driven and self-motivated. Perks : 20 vacation days Comprehensive health and extended health benefits Unlimited sick days Stock options We encourage applicants from all backgrounds to apply, even if you don't meet all the listed qualifications. We are an inclusive and diverse company.

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