Analog Group
Software Engineer
Analog Group, Oklahoma City, Oklahoma, United States,
Our Client is a Boston based company that builds chips for artificial intelligence computing. Their architecture leverages unique properties of light to enable fast and efficient inference and training engines. If you’re a collaborative software 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 then we would like to hear from you.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 framework 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.Job Description:
Develop systems software for integration between deep learning packages (e.g. Tensorflow) and hardware accelerators.Work with the compiler and machine learning teams to enable low-latency, high-throughput deep learning computation.Design a runtime environment that accepts neural networks, allocates memory, and manages instructions.Develop firmware for managing board level hardware resources.Implement Linux device driver for an offline ASIC/FPGA accelerator with high-speed interconnect.Qualifications:
BS or higher in computer/software engineering, electrical engineering, or related field.1-2 years of experience with driver and kernel side development is preferred.Strong understanding of computer architecture and hardware-software integration.Experience developing frameworks for offline accelerators e.g. FPGA or GPU.Highly proficient in C/C++ with good software engineering habits.
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Develop systems software for integration between deep learning packages (e.g. Tensorflow) and hardware accelerators.Work with the compiler and machine learning teams to enable low-latency, high-throughput deep learning computation.Design a runtime environment that accepts neural networks, allocates memory, and manages instructions.Develop firmware for managing board level hardware resources.Implement Linux device driver for an offline ASIC/FPGA accelerator with high-speed interconnect.Qualifications:
BS or higher in computer/software engineering, electrical engineering, or related field.1-2 years of experience with driver and kernel side development is preferred.Strong understanding of computer architecture and hardware-software integration.Experience developing frameworks for offline accelerators e.g. FPGA or GPU.Highly proficient in C/C++ with good software engineering habits.
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