AI Embedded Software Engineer

DIALOG 

📍 Center District, Israel 🇮🇱

full-time
senior
hybrid
Posted —

Key Skills

C++NPUDSPAIoptimization

Industry

SemiconductorConsumer Electronics

Job Description

A high-profile Global Tech Leader specializing in advanced wireless communication, smart sensing, and AI-driven semiconductor solutions.


The company’s AI division is a global powerhouse of innovation, designing next-generation Neural Network Processors (NPU) and Vision DSPs.


By integrating high-end IP design with sophisticated embedded software, the organization enables high-performance, energy-efficient AI inference across hundreds of millions of devices.


Located in Central Israel (adjacent to major transit hubs), the company offers an elite R&D environment with a flexible hybrid work model (2 days WFH).


Responsibilities-

  • Software Architecture Design: Defining and building critical components of the Edge AI software stack, ensuring seamless execution of neural networks under strict power, memory, and latency constraints.
  • Performance Optimization: Leading the optimization of inference performance (latency, throughput, memory footprint) for complex edge deployments.
  • HW–SW Co-Design: Collaborating with hardware and system architects to influence future NPU architectures and drive silicon-level innovations.
  • Silicon Bring-up & Evaluation: Taking a proactive role in IP evaluations and silicon bring-up, identifying complex hardware/software bottlenecks and defining development methodologies.
  • Technical Leadership: Mentoring junior engineers and leading high-impact technical initiatives within a multidisciplinary R&D group.
  • Expert-Level Development: Hands-on development in C/C++ within a high-performance embedded environment.


Requirements-

  • Technical Seniority: Significant experience in Embedded Software Engineering, with a deep focus on C/C++ – Mandatory.
  • Domain Expertise: Proven track record in developing software stacks for AI Accelerators, NPUs, or DSPs – Mandatory.
  • Optimization Mastery: Deep understanding of performance constraints (Latency, Power, Memory) in Edge AI or mobile environments – Mandatory.
  • Hardware/Software Synergy: Experience in HW–SW co-design and a solid understanding of computer architecture – Mandatory.
  • System-Level Vision: Ability to architect complex software systems and influence hardware roadmaps.