Embedded AI OS Architect - Deterministic Edge & Performance

microTECH Global Limited

Pisa

On-site

EUR 100,000 - 200,000

Full time

14 days+

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Job summary

microTECH Global Limited in Pisa, Italy seeks an Embedded AI OS Architect to design OS and middleware that merges deterministic execution with agentic AI. You will optimize performance of embedded hardware and shape resource scheduling for AI model inference.

The role requires a MSc/PhD in CS/CE/EE, deep Linux kernel or RTOS knowledge, ARM/RISC-V expertise, strong C/C++ and driver experience, and edge AI tooling such as TensorFlow Lite.

Qualifications

  • MSc. or Ph.D. in Computer Science, Computer Engineering, or Electronic Engineering.
  • Deep knowledge of Linux kernel internals and/or RTOS (e.g., Zephyr, FreeRTOS, ERIKA).
  • Strong understanding of ARM or RISC-V ISA, SoCs, MMUs, cache/memory hierarchies.
  • Excellent C/C++ programming skills, with experience in Assembly and device driver implementation.
  • Experience with machine learning (CNN, DNN, SVM) and edge AI tooling.

Responsibilities

  • Architecture & AI Integration: Design OS and middleware architectures that integrate deterministic execution with novel agentic AI technologies.
  • Performance Optimization: Analyze and reduce end-to-end latencies across embedded hardware (CPUs, GPUs, NPUs, memory, network).
  • Resource Scheduling: Develop core OS tech to support efficient AI model inference and heterogeneous resource scheduling.

Skills

C/C++ programming
Assembly
Linux kernel internals
RTOS (Zephyr/FreeRTOS/ERIKA)
Arm or RISC-V
Edge AI/ML
Device driver implementation

Education

MSc or PhD in Computer Science/Engineering

Tools

TensorFlow Lite

Job description

microTECH Global Limited in Pisa, Italy seeks an Embedded AI OS Architect to design OS and middleware that merges deterministic execution with agentic AI. You will optimize performance of embedded hardware and shape resource scheduling for AI model inference.

The role requires a MSc/PhD in CS/CE/EE, deep Linux kernel or RTOS knowledge, ARM/RISC-V expertise, strong C/C++ and driver experience, and edge AI tooling such as TensorFlow Lite.

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