ABOUT THE JOB

Venture , a public listed company in SGX, is a leading global provider of technology services, products and solutions with established capabilities spanning marketing research, design, research and development. Over the years, Venture has built know-how and intellectual property with expertise in several technology domains. These include life science & genomics, molecular diagnostics, medical devices and equipment, healthcare and wellness technology, lifestyle consumer technology, health improvement products, instrumentation, test and measurement technology, networking and communications, fintech, as well as computing, printing and imaging technology.
Headquartered in Singapore, the Group comprises over 30 companies with global clusters in Southeast Asia, Northeast Asia, America and Europe, and employs over 12,000 people globally.
At Venture, our people are our most valuable asset. We are committed to unifying culture, encouraging innovation, and harnessing the collective strengths and synergies of our human capital to deliver compelling differentiation, advancing Venture’s position as a leading global provider of technology solutions, products and services.
We’re looking to add a Software Engineer - Full Stack AI in Singapore . The position is based in our HQ at Ang Mo Kio .

WHAT SKILLS AND EXPERIENCES ARE WE LOOKING FOR?

• Possess at least a Degree in Computer Science, Electrical and Electronics Engineering.
• A minimum of 3 years of hands-on experience in vision AI pipelines (CV projects in robotics, manufacturing or IoT preferred).
• Familiar with Python, Javascript, Machine Learning, AI (CNN, RNN), Tensorflow, Pytorch.
• Front-end skills (React/Flask/Django) to prototype user interfaces.
• Ability to write efficient C or C++ code for embedded systems, especially with RTOS exposure.
• Knowledge in Electron Framework would be an advantage.
• Good understanding in cloud AI services (AWS SageMaker) and containerization (Docker/Kubernetes) would be an advantage.

• Develop full-stack applications (front-end interfaces + back-end APIs) to manage image data pipelines, model training, and inference.
• Deploy models across platforms: cloud services, desktop applications, and embedded systems.
• Work with the hardware team to optimize models for low-latency, resource-constrained environments (e.g., TensorRT, ONNX Runtime, or OpenVINO).
• Contribute to building tools for dataset preprocessing, augmentation, and annotation