Machine Learning Hardware Engineer / Scientist

Machine Learning algorithms targeting FPGAs or ASICs., Convolutional Neural Networks / LSTMs / Transformers, PyTorch / Keras / TensorFlow, Xilinx or Intel FPGA High-Level Synthesis tools
Full Time
$140,000 - $180,000
Work from home not available Travel not required

Job Description

Clearance: Must be eligible to obtain and maintain a high level security clearance.

We are a long-time pioneer of research investigating Field Programmable Gate Arrays.
Spanning the days of homogeneous logic devices to today’s billion transistor System on Chip devices, we have led the way from being the first to implement application level partial runtime reconfiguration, investigating 3D FPGA architectures, developing Autonomous System on Chip architectures, releasing open source CAD tools which target real physical devices, IP to address software / hardware co-design complexity and continues today with research ranging from developing programming models for next generation industry devices to conducting experiments on the International Space Station.
Today, we are addressing our nation’s challenges in big data, hardware cybersecurity, trusted systems, cognitive radio and more.

We are looking for highly talented, motivated researchers to lead and impact state of the art research and development in the areas of Machine Learning (ML) and Reconfigurable Computing.
This position will lead research in algorithm development for custom ML tools which target FPGA and ASIC front end design.
These tools solve challenging problems in algorithm development of Machine Learning architectures targeting FPGA and ASIC platforms, including embedded and cloud FPGA-based systems.
The position will also investigate hardware security, high level abstraction for hardware design, and machine learning acceleration for critical systems.
Realize effectiveness of solutions on physical FPGAs and custom ASIC fabrication.
Lead research, propose major innovations, collaborate with peers within the group and across ISI, publish results in top tier conferences, and contribute to or lead proposals.

Required Qualifications

• PhD in Computer Engineering, Electrical Engineering, or Computer Science with expertise in Machine Learning algorithms and computer architectures targeting FPGAs or ASICs.
• Previous publication, patents, or other displays of innovation in machine learning with FPGAs, such as Convolutional Neural Networks, LSTMs, and Transformers.
• Expertise with Machine Learning Toolkits, such as PyTorch, Keras, and TensorFlow
• Experience with Xilinx or Intel FPGA High-Level Synthesis tools.

Preferred Qualifications:

• Five years of experience designing, developing, implementing, and debugging Machine Learning applications for FPGAs, including Xilinx Virtex7 or newer architectures. Experience with Intel and Stratix-10 devices also desirable.
• Five years of Python and C++/Java development experience, including contributions to large-scale software projects, commercial or open-source.
• Training and Inference with publicly available models (ResNet, VGG) and the development of custom models targeting FPGAs.
• Use of FPGA-based Cloud Environments, such as Amazon AWS F1, Nimbix Cloud, Azure Cloud, Xilinx Alveo Accelerators.
• Proficiency in software cross-compiling and cross-debugging.
• Experience with multi-processor system-on-chip, embedded systems software (Linux, cross-compilers) and Python productivity for FPGAs (i.e. Pynq).
• Experience leading or contributing to proposals a significant plus.

Minimum Education: Master’s degree, Combined experience/education as substitute for minimum education
Minimum Experience: 3 years Minimum Field of Expertise: Knowledge of research processes and computer science.

Posted By

Ashwin Kumar

309 Dundee Road Barrington, IL, 60010

Dice Id : 91099295
Position Id : 6472889
Originally Posted : 2 weeks ago
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