Lead Embedded AI Software Engineer

About the role

We are seeking a Lead Embedded AI Software Engineer to design and deploy AI‑enabled embedded systems on a multi‑vendor AI chiplet platform. You will work at the intersection of hardware, low‑level AI accelerators and complex software stacks to create safe, secure and efficient AI pipelines for automotive and industrial applications.

Key responsibilities

• Define the embedded AI software architecture for multi‑vendor AI chiplet platforms.
• Drive host‑side CPU orchestration and code optimisation.
• Design and implement hardware‑software interfaces (HSI) using UCIe‑based communication, drivers and access‑management layers.
• Implement and optimise AI inference pipelines in C++ and OpenVX, targeting performance, latency and resource constraints.
• Develop safety‑ and security‑monitoring components for AI workloads (health checks, secure execution, anomaly detection).
• Advise on model partitioning, slicing, retraining or fine‑tuning, and quantisation‑aware deployment strategies.
• Lead initial deployment and tuning of AI models on embedded targets, considering memory, bandwidth and power budgets.

Required profile

• Strong proficiency in C++ and embedded systems programming, with experience in real‑time or safety‑critical environments.
• Deep expertise in OpenVX, OpenCL and/or GPU compute frameworks such as Vulkan.
• Solid understanding of AI chiplets, heterogeneous acceleration and high‑speed interconnects (e.g., UCIe) and host‑side drivers.
• Familiarity with AI accelerator toolchains and neural‑network model mapping to AI chiplets.

Required skills

• C++
• Embedded systems programming
• Real‑time / safety‑critical development
• OpenVX
• OpenCL
• Vulkan (GPU compute)
• AI chiplet architectures
• UCIe high‑speed interconnects
• Host‑side driver development
• AI accelerator toolchains
• Neural network model mapping and quantisation