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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Embedded AI Software Engineer Mid-Level - **Company:** Robert Bosch GmbH - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computing Platforms, Artificial Neural Networks, Computer Vision, AUTomotive Open System Architecture (AUTOSAR), C++ (Programming Language), Code Generation, Communications Protocols, Data Visualization, Digital Architecture, Embedded Software, OpenCL, Prism (Software), Data Streaming, Image Acquisition, ONNX (Open Neural Network Exchange) Format, Hardware Acceleration, Machine Learning Operations, TensorRT - **Published:** July 14, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p48zsf4hi6 ## About the Role * 4-7 years of experience in embedded software engineering, with a strong focus on AI, computer vision, or heterogeneous computing platforms. * Strong proficiency in C++ and embedded systems programming, with experience in real-time or safety-critical environments. * Expertise in OpenVX, OpenCL, and/or GPU compute frameworks (e.g., Vulkan), especially for computer vision and/or AI pipelines. * Good understanding of AI chiplets, heterogeneous acceleration, and high-speed interconnects (e.g., UCIe) and host-side drivers. * Experience with AI model deployment on embedded targets, including model partitioning, slicing, quantization, and toolchain integration (e.g., TensorRT, ONNX-Runtime, vendor-specific stacks). * Familiarity with AI accelerator toolchains and neural network models to AI chiplet mapping. * Knowledge of OpenVX glue-code generators / AI glue frameworks and experience in extending such code generators is a strong plus. * Understanding of safety- and security-critical requirements (e.g., ISO 26262, AUTOSAR, or industrial safety standards) and how to monitor AI workloads in such environments. * Good written and verbal communication skills, with the ability to document architecture, APIs, and integration guidelines. ## 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., * 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. ## Related Videos - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Software is the New Fuel, AI the New Horsepower - Pioneering New Paths at Mercedes-Benz](https://www.wearedevelopers.com/videos/1388-software-is-the-new-fuel-ai-the-new-horsepower-pioneering-new-paths-at-mercedes-benz) ## Related Articles - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)