Job Description
We are looking for a  Embedded AI SW Engineer  to design and deploy AI‑enabled embedded systems around a multi‑vendor AI chiplet platform. In this role, you will bridge hardware, low‑level AI accelerators, and complex software stacks to enable sustainable, safety‑ and security‑aware AI pipelines in embedded automotive or industrial environments.  Key responsibilities: Execute embedded deployment of neural network models, including model slicing, retraining (or fine‑tuning) strategies, and quantization‑aware deployment.  Deployment and tuning of AI models on embedded targets, including memory, bandwidth, and power‑aware partitioning.  Integrate selected AI accelerator toolchains into the internal tool environment, enabling end‑to‑end model development, optimization, and deployment.  Extend and evolve AI Glue (OpenVX glue‑code generator) to automate mapping of AI graphs and kernels to heterogeneous chiplets and backends.  Integrate and visualize AI pipeline behavior and performance via PRISM‑based or similar visualization tools.  Develop and optimize OpenVX accelerator backends and kernels for the Bosch chiplet project, including computer vision pipelines and different AI workloads.  Implement and tune OpenCL and Vulkan kernels for sensor and image processing pipelines (image acquisition and pre-processing) on GPU and hardware accelerators.  Collaborate with hardware teams to define and refine chiplet‑specific APIs, memory models, and communication protocols (e.g., UCIe, host‑side drivers).  Ensure sensor‑to‑AI data flows are optimized for bandwidth, latency, and determinism, including safety‑critical constraints where applicable.  1-3 years of experience in embedded software engineering, with a strong focus on AI,
