We are looking for algorithm and optimization experts to help unlock the potential of our unique spatial compute architecture. In this role you would develop efficient solutions to the hard graph optimization problems involved in allocating chip resources for neural network inference acceleration. These challenges include graph partitioning scheduling and place and route optimization. Additionally you would develop profiling and visualization tools and collaborate with other teams in identifying performance bottlenecks and conceiving creative solutions.
Requirements
Computer Science Engineering or related degree
5 years of SW development experience
Creative problem solver passionate about solving hard problems
Expertise in combinatorial and graph optimization algorithms
Strong C and python development skills
Experience optimizing code for highperformance and delivering it to production
Excellent communication and collaboration skills
Preferred Skills & Experience
Masters or PhD in Computer Science Engineering or related field
EDA or FPGA place and route experience
Relentless focus on software quality and testing
Proficient with python datascience libraries (pandas numpy bokeh)
Familiar with neural net frameworks tensorflow or pytorch
Experience working with continuous integration systems
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