Machine Learning Compiler Engineer at Lightmatter
Boston, Massachusetts, United States
🇺🇸 (Posted Jun 6 2018)
About the company
Lightmatter builds chips for artificial intelligence computing. Our architecture leverages unique properties of light to enable fast and efficient inference and training engines.
Lightmatter builds chips for artificial intelligence computing. Our architecture leverages unique properties of light to enable fast and efficient inference and training engines. If you're a collaborative engineer or scientist who has a passion for innovation, solving challenging technical problems and doing impactful work...work like building the world's first optical computers, consider joining the team at Lightmatter!
We are looking for talented software engineers to help us build the next generation of AI processors.
In this role, you will be responsible for developing highly optimized computational methods for deep learning. You'll be working with deep learning scientists, as well as digital, analog, and photonic designers, to implement the features needed to accelerate the next generation of machine learning algorithms.
Develop and implement compiler tools that translate deep learning packages (e.g. Tensorflow, Caffe, MXNET, or Theano) to machine language.
Analyze, craft, and implement compiler and linear algebra optimization techniques for neural networks.
Work with digital and analog engineers to define instruction sets that enable low-latency, high-throughput deep learning computation.
Evaluate trade-offs and optimize between different software-hardware architectures in terms of performance and efficiency.
Skills & requirements
MS or higher in computer science, computer engineering, electrical engineering, or related field.
Highly proficient in LLVM compiler infrastructure and other modern compiler design.
Highly proficient in clang, C/C++ with a strong software architecture background.
Proficient in hardware-software integration with accelerated multi-threaded and concurrent programming.
Understanding of the different computing architectures, e.g. CPU, GPU, FPGA.
Experience with maintaining a large codebase with good software engineering habits.
Instructions how to apply
see the website
[ job website
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