job description
Join Silitech Technology Corporation as an AI Vision Engineer and pioneer the future of computer vision and machine learning in a dynamic, innovation-driven environment. Based in the vibrant tech hub of Canggu, Bali, you’ll work on groundbreaking projects that leverage deep learning, image processing, and AI to solve real-world challenges.
This role is perfect for a passionate engineer with a strong foundation in Electrical/Electronics, Computer Science, or Data Science, coupled with hands-on experience in Python, OpenCV, TensorFlow, or PyTorch. You’ll collaborate with cross-functional teams to develop and deploy scalable AI vision systems that push the boundaries of what’s possible.
At Silitech, we foster a culture of creativity, continuous learning, and impact. If you’re eager to shape the next generation of AI-powered solutions in a tropical paradise, this is your opportunity to make a difference.
Responsibility
- Design, develop, and optimize computer vision algorithms for object detection, image segmentation, and pattern recognition.
- Implement and fine-tune deep learning models (CNNs, RNNs, Transformers) using frameworks like TensorFlow, PyTorch, or Keras.
- Collaborate with hardware teams to integrate AI vision systems into embedded devices or cloud-based platforms.
- Preprocess and augment large-scale image/video datasets to improve model accuracy and robustness.
- Deploy and monitor AI models in production, ensuring scalability, latency, and real-time performance.
- Conduct research to stay ahead of emerging trends in AI, machine learning, and computer vision.
- Debug and optimize existing vision systems for efficiency, speed, and resource utilization.
- Document technical processes, architectures, and best practices for team knowledge sharing.
Qualifications
- Bachelor’s or Master’s degree in Electrical/Electronics Engineering, Computer Science, Data Science, or a related field.
- Proven experience (2+ years) in Python programming and machine learning frameworks (TensorFlow, PyTorch, OpenCV).
- Strong understanding of computer vision techniques (e.g., feature extraction, SLAM, 3D reconstruction).
- Experience with data preprocessing, annotation, and augmentation for vision datasets.
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus.
- Knowledge of edge AI deployment (e.g., NVIDIA Jetson, Raspberry Pi, or FPGA acceleration) is advantageous.
- Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
- Strong communication skills in English, with the ability to articulate complex technical concepts.