About The Position

Ceva’s AI Division develops machine-learning and generative-AI architectures for edge devices and cloud inference, including neural network processors (NPU), vision DSPs, and advanced AI algorithms. Its technology supports smartphones, tablets, automotive, robotics, surveillance cameras, and other edge AI and 5G systems. The AI & DSP Processor Simulators Team Lead will lead a team of 3–5 engineers responsible for designing, optimizing, and developing features for an NPU/DSP simulator used by internal engineering teams and Ceva customers. The role involves developing in C/C++ using object-oriented programming on Linux and Windows, and working with architecture, algorithms, system, VLSI, and QA teams, including remote design centers.

Requirements

  • B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related technical field.
  • At least 8 years of hands-on software engineering experience.
  • At least 2 years in managerial positions leading software teams.
  • Strong C/C++ programming and debugging skills, including object-oriented design of complex embedded software systems.
  • Comfort working in an existing codebase and making modifications.
  • Strong scripting skills.
  • Enthusiasm for machine learning, AI, and computer vision.
  • Excellent problem-solving skills and attention to detail.
  • Independent, self-motivated, and curious, with good communication skills and the ability to manage time and prioritize tasks.

Nice To Haves

  • Experience with Python and deploying AI/ML models.
  • Experience developing hardware simulators or modeling internal mechanisms of ASIC platforms.
  • SystemC/TLM experience.
  • Experience developing in Linux environments.

Responsibilities

  • Lead a team of 3–5 engineers responsible for the NPU/DSP simulator.
  • Design and develop simulation software for Ceva’s NPU and DSP platforms within an agile software organization.
  • Analyze and optimize simulator performance and accuracy across multiple Ceva processor architectures.
  • Debug a large existing codebase and deliver solutions to complex software challenges.
  • Collaborate with architecture, algorithms, system, VLSI, and QA teams, including remote design centers.
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