Salary: RM 3,800 – RM 5,500 per month

Key Responsibilities

Design, develop, train, evaluate, and deploy Machine Learning and Deep Learning models using Python.
Develop AI solutions for object detection, image classification, image segmentation, anomaly detection, and industrial inspection.
Implement and optimize deep learning architectures using TensorFlow, PyTorch, or Keras.
Apply transfer learning, fine-tuning, and data augmentation techniques to improve model accuracy and robustness.
Design and implement advanced neural network architectures including CNNs, Vision Transformers (ViTs), RNNs, Autoencoders, GANs, and Transformer-based models.
Build scalable training pipelines supporting single-GPU, multi-GPU, and distributed training (DDP).
Optimize AI models for high-performance inference using CUDA, TensorRT, ONNX, and cuDNN.
Perform image preprocessing and enhancement using OpenCV or similar image processing libraries.
Prepare, clean, annotate, and manage datasets for model training and validation.
Evaluate model performance using appropriate metrics and continuously improve model accuracy and inference speed.
Collaborate with software engineers to integrate AI models into desktop, embedded, or cloud-based applications.
Participate in code reviews, technical discussions, and maintain technical documentation.

Required Skills

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Electronics, or a related field.
Minimum 1 years of hands-on experience in Machine Learning, Deep Learning, or Computer Vision.
Strong programming skills in Python.
Strong understanding of Machine Learning and Deep Learning concepts.
Hands-on experience with PyTorch, TensorFlow, or Keras.
Strong knowledge of Computer Vision using OpenCV.
Experience developing one or more of the following:
- Object Detection (YOLO, Faster R-CNN, SSD)
- Image Segmentation (U-Net, Mask R-CNN, YOLO Segmentation)
- Image Classification
- Anomaly Detection (PatchCore, Autoencoders, EfficientAD, or similar)
Good understanding of image processing techniques such as filtering, thresholding, morphology, feature extraction, and image enhancement.
Experience with GPU computing and model optimization using CUDA-enabled environments.
Familiarity with Linux and Windows development environments.
Strong analytical, debugging, and problem-solving skills.
Good communication and teamwork skills.

Preferred Skills (Good to Have)

Experience with NVIDIA TensorRT, ONNX Runtime, CUDA, and cuDNN.
Experience with distributed training using DDP or multi-GPU environments.
Familiarity with Docker and containerized AI deployments.
Experience with NVIDIA Jetson platforms or edge AI deployment.
Familiarity with Git and version control systems.
Exposure to HALCON or other industrial machine vision libraries.
Experience integrating AI models into production software applications.
Experience working on manufacturing, industrial automation, quality inspection, or machine vision projects.
Basic knowledge of cloud platforms such as AWS, Azure, or Google Cloud is an added advantage.

What We Offer

Opportunity to work on cutting-edge AI, Machine Learning, and Computer Vision technologies.
Exposure to industrial automation, machine vision, and smart manufacturing solutions.
Hands-on experience with high-performance GPU computing and AI optimization.
Opportunity to work with the latest Deep Learning and Generative AI models.
Collaborative engineering environment with continuous learning and career growth.
Opportunity to develop production-ready AI solutions deployed in real-world manufacturing environments.

Nice to Have

Candidates with experience in any of the following will have an added advantage:

Summary

See also