- AI Algorithm Engineering and Embedded Integration
- Develop and optimize AI models tailored for industrial vision (X-ray) and signal analysis (checkweighing, metal detection), and take charge of their engineering encapsulation and integration.
- Deeply integrate trained models into existing host software architectures using C++ libraries, ONNX Runtime, TensorRT, or custom inference engines.
- Design and implement data pipelines for real-time communication with image acquisition cards, PLCs, sensors, and other hardware to ensure stable, low-latency input for AI modules.
- Industrial Host Software Development and Architecture
- Lead or deeply participate in the development, maintenance, and refactoring of main control programs for device control, data processing, and Human-Machine Interface (HMI) using C++/C# or Python.
- Build high-performance, high-reliability multi-threaded/real-time software systems to manage concurrent tasks such as image processing, AI inference, data logging, and UI rendering.
- Develop core modules for device configuration, algorithm parameter management, result visualization, and report generation, ensuring seamless synergy with AI functionalities.
- Full-Stack Delivery of Edge Intelligence Systems
- Independently complete the entire lifecycle from requirements analysis, software design, and coding to testing and on-site deployment support. You deliver a deployable, runnable, and maintainable software functional package rather than just a model file.
- Optimize the overall performance and resource footprint of software and AI models on edge computing units, resolving real-world issues related to memory, CPU, and GPU utilization.
- Write production-grade code and establish rigorous unit testing, integration testing, and logging systems to ensure compliance with the stringent stability and reliability requirements of the industrial sector.
- Cross-Domain Collaboration and Productization
- Work closely with mechanical, electrical, and hardware teams to understand equipment principles and jointly define interface specifications between software and AI.
- Collaborate with Product Managers and UI/UX Designers to transform complex AI capabilities into intuitive, easy-to-use operating interfaces and user experiences.
- Basic Requirements
- Bachelor’s degree or above in Computer Science, Software Engineering, Automation, or a related field, with 3+ years of experience in industrial host computer or embedded software development.
- Strong Software Engineering Skills: Proficient in C++, C# or Python, with a solid foundation in Object-Oriented Programming (OOP), design patterns, data structures, and algorithms. Capable of independently handling the development of core modules.
- AI Integration Experience: Practical experience in deep learning development using PyTorch/TensorFlow, with at least one successful case of integrating and deploying a trained model into a functional software product. Familiar with model conversion, optimization, and inference acceleration.
- Systems Thinking: Deep understanding of the Software Development Life Cycle (SDLC), with excellent coding style, documentation habits, and debugging skills. Experience in multi-threading, network communication, and hardware interface programming is preferred.
- Preferred Qualifications
- Experience in host software development for machine vision, industrial automation, medical devices, or inspection equipment.
- Familiarity with industrial communication protocols and experience developing high-performance applications in Windows/Linux real-time environments.
- Experience with desktop application frameworks and knowledge of front-end interaction technologies.
- A strong passion for AI with proven success in landing AI solutions to solve practical engineering problems.
- Familiarity with Agile development methodology (e.g. SAFe, Scrum).
- Competitive compensation & benefit package
- Possibility to work in an international environment with multicultural team
- Interesting and challenging career in a successful leading global organization
- Trainings and professional development
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