Key Responsibilities
- Software Architecture & Development: Design, build, and maintain production-grade software modules for image acquisition, real-time image processing pipelines, and feature extraction.
- Algorithm Implementation: Code and optimize advanced computer vision algorithms for wafer-to-probe alignment, die sorting pattern recognition, and micro-defect identification.
- Hardware & API Integration: Develop driver-level interfaces and software APIs to seamlessly connect high-speed industrial cameras, frame grabbers, and motion controllers with the main tester platform.
- AI & Machine Learning Deployment: Optimize and deploy pre-trained deep learning models (e.g., CNNs) onto edge hardware using acceleration libraries for real-time defect classification.
- Performance Tuning: Optimize code execution, multi-threading, and GPU/CPU memory allocation to ensure ultra-low latency processing capable of matching high-throughput fab speeds.
- Testing & Quality Assurance: Write rigorous unit tests, integration tests, and hardware-in-the-loop (HIL) simulations to guarantee software robustness during continuous cleanroom production.
- Version Control & CI/CD: Maintain version control, document software architecture, and integrate modules into the team's automated build and continuous deployment pipelines.
Required Skills and Qualifications
- Education: Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a highly technical related field.
- Experience: Minimum 5+ years of professional software engineering experience developing computer vision or machine vision applications.
- Core Programming: Advanced proficiency in C++ (Modern C++14/17/20 preferred) and/or Python and C#, with strong object-oriented programming (OOP) principles.
- Vision Frameworks: Extensive experience with core vision and imaging libraries such as OpenCV, Halcon, MIL, or Point Cloud Library (PCL).
- High-Performance Computing: Understanding of multi-threading, concurrency, and performance optimization tools (e.g., NVIDIA CUDA, TensorRT, OpenVINO, or Intel IPP).
- Software Ecosystem: Proven experience with Git, CMake, and working within Linux or Windows development environments.
Preferred Qualifications
- Experience with camera communication standards like GigE Vision, USB3 Vision, Camera Link, or CoaXPress.
- Direct background working on semiconductor equipment (e.g., wafer probers, wire bonders, pick-and-place systems).
- Familiarity with UI frameworks like Qt or .NET for data and image visualization.
How To Apply:
Interested candidate, please submit your updated resume in MS WORD Format to Terry Ng, email – [Confidential Information]
EA Personnel Reg. No. R1107654, Achieve Career Consultant Pte Ltd EA Licence No. 05C3451
We regret that only shortlisted candidates will be notified. Thank you for your interest in this opportunity.
