Lead Software Engineer

Ann Arbor, MI, US

Who we are
MemryX, Inc. is an AI semiconductor startup company headquartered in Ann Arbor, Michigan, with branches in Taipei and Hsinchu, Taiwan. We develop highly scalable and innovative AI accelerator chips that offer high performance, low energy, and customer ease of implementation for embedded Edge AI vision-based applications and real-time data processing. Company has working HW & SW for customer sampling, with production designs in the pipeline, and a system architecture designed a future of neuromorphic computing. MemryX is backed by excellent VC funding and is currently in a stage of rapid growth.

What you will be doing

  • Build, inspire, mentor and retain high-performing global software engineering team responsible for delivering MemryX’s breakthrough product
  • Establish software engineering best practices for development, testing, documentation, and technical reviews
  • Architect, design, and maintain our neural SDK to integrate with the current neural compiler and hardware solutions.
  • Build and maintain customer-facing software tools.
  • Collaborate with senior leadership on strategic discussions for product features and roadmap
  • Participate in customer meetings and building out the partner ecosystem

What we expect to see

  • MS/PhD in Computer Science with 15+ years of experience in Embedded Systems Design, SW architecture, SW/HW co-design
  • Hands-on experience on SDK development and ability to master new technologies and complex systems
  • Proven leadership skills and track record in successfully driving technical/architectural solutions to products
  • Excellent presentation skills to C-level executives, Board, customers and technical audience
  • Knowledge of the fundamental AI/neural-networks concepts
  • Strong programming proficiency and excellent object-oriented design skills
  • Self-driven with the ability to motivate and lead the team

What we would be happy to see

  • Hands-on experience with ML frameworks (TensorFlow/Keras, PyTorch, or ONNX).
  • Computer vision, ADAS, and robotics neural network models understanding.
  • Application-specific accelerators understanding.
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