Lead Embedded AI Software Engineer

About Bosch Engineering Center Cluj

Since its establishment in 2013, Bosch Engineering Center Cluj plays an essential role in the current transformation of the mobility sector. Through its extensive expertise in software, hardware & mechanical engineering, reliability engineering, as well as sales planning, the center contributes to the development of innovative products and services based on artificial intelligence (AI) applied in the fields of automated driving, electric and connected mobility. Thanks to the diverse professional and personal development opportunities, flexible working conditions, modern offices and laboratories in Cluj-Napoca, Jucu, Bucharest and Sibiu, we are one of the most desired employers among engineers and IT professionals in Romania.

Our promise to our colleagues is rock-solid: we grow together, we enjoy our work, and inspire each other. Join us and see the difference.

We are looking for a Lead Embedded AI Software 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.

Responsibilities

Define the embedded AI software architecture for multi‑vendor AI chiplet platforms.; Drives host‑side Application processing unit (CPU) orchestration and code optimizations.; Design and implement efficient hardware‑software interfaces (HSI) between AI chiplets and host systems via UCIe‑based communication, drivers, and access‑management layers.; Implement and optimize embedded AI inference pipelines using C++ and OpenVX, targeting performance, latency, and resource constraints.; Develop and maintain safety‑ and security‑monitoring components for AI workloads (e.g., health checks, secure execution, anomaly detection).; Consults on embedded deployment, including model partitioning, slicing, retraining (or fine‑tuning) strategies, and quantization‑aware deployment.; Lead the initial deployment and tuning of AI models on embedded targets, including memory, bandwidth, and power‑aware partitioning.

Requirements

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 (e.g., Vulkan), especially for computer vision and/or AI pipelines.; 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 models to AI chiplet mapping.; Strong systems‑thinking and cross‑layer design skills (from sensor data acquisition and pre-processing to inference and post-processing).; Strong collaboration skills with hardware architects, firmware, safety/security, and algorithm teams.; Good written and verbal communication skills, with the ability to document architecture, APIs, and integration guidelines.

Benefits

25 Days of annual leave , because work-life balance is essential to us,; Flexible working hours.