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Baidu

Machine Learning System Hardware Architect

Department
Engineering
Job Type / Location
Sunnyvale
Experience Required
5+ years
Posted On

About the Role

We are looking for a world-class Machine Learning System Architect (HW) to join our SoC team at Baidu’s Sunnyvale office. The successful candidate will be a motivated self-starter who will thrive in this highly technical environment. Your job responsibilities as a Machine Learning System Architect will help the team to architect and create high-performance machine learning silicon and connect thousands of Kunlun Accelerators together for distributed AI training tasks.

Responsibilities

  • Create differentiated architectural innovations for Baidu’s Kunlun AI SoC roadmap.
  • Architect, simulate, and design amazing machine learning solutions for our AI machine learning products.
  • Develop system-level ML architectures that push the boundaries of performance, power, and latency; collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance.
  • Monitor industrial and academic trends in artificial intelligence and determine where they should intersect our roadmaps.
  • Drive partnerships for access to the most advanced AI technologies.
  • Evaluate the power, performance, and cost of prospective architecture and subsystems.
  • Build scalable tools for modeling and performance evaluation.
  • Engage with system and application software engineers to ensure optimization of the entire hardware/software stack.
  • Engage with SoC design, verification, and validation engineers to realize the architecture.

Qualifications

  • Knowledge of Machine Learning market, technological and business trends, software ecosystem, and emerging applications.
  • Proven track record 5+ years architecting hardware solutions for Machine Learning, acceleration and optimization.
  • Experience with deep learning frameworks including TensorFlow, PyTorch, PaddlePaddle, etc.
  • Strong track record of outreach to ML researchers and application developers.
  • Experience with CPUs, GPUs, memory systems, and accelerators.
  • Experience with performance simulation and modeling in C++.
  • Experience with SoC interconnects and NoCs.
  • Experience with area, frequency, and power optimizations.
  • Familiarity with video, DSP, Ethernet, and PCIe.
  • MS or PhD in Electrical or Computer Engineering.
  • Excellent communication skills in both English and Chinese.

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