AI/ML - Computer Vision Engineer
Stockbit
Software Engineering, Data Science
Indonesia
Posted on Mar 7, 2026
About The Role
Work with Stockbit to integrate AI and Machine Learning solutions that drive ROI, not hype. Stockbit’s rich ecosystem opens up projects across digital marketing, creative teams, operations, KYC, social media moderation, and many more. We are looking for a Computer Vision Engineer with strong software engineering discipline and hands-on deployment experience. You will build and ship production-grade vision systems while owning the deployment infrastructure for the AI department.
Responsibilities
Candidates must demo 2–3 previous projects during the HR interview — slides or presentations are acceptable, GitHub is a plus but not required in case the projects are confidential. You must be able to explain what you've built to a non-technical person.
Work with Stockbit to integrate AI and Machine Learning solutions that drive ROI, not hype. Stockbit’s rich ecosystem opens up projects across digital marketing, creative teams, operations, KYC, social media moderation, and many more. We are looking for a Computer Vision Engineer with strong software engineering discipline and hands-on deployment experience. You will build and ship production-grade vision systems while owning the deployment infrastructure for the AI department.
Responsibilities
- Develop and maintain computer vision solutions across Stockbit’s product ecosystem.
- Fine-tune and optimize models for production use cases.
- Build data pipelines for image preprocessing, augmentation, and evaluation.
- Write clean, testable, well-documented production code.
- 3–5 years of hands-on Software Engineering and Computer Vision experience.
- Proficiency in Python and Go.
- Hands-on experience with image processing tools (OpenCV, Pillow, or similar).
- Experience with object detection frameworks (YOLO, Faster R-CNN, or similar).
- Familiarity with OCR tools and pipelines
- Experience fine-tuning deep learning models in PyTorch or TensorFlow.
- Machine learning fundamentals with hands-on scikit-learn experience.
- Docker proficiency for managing development and training environments.
Candidates must demo 2–3 previous projects during the HR interview — slides or presentations are acceptable, GitHub is a plus but not required in case the projects are confidential. You must be able to explain what you've built to a non-technical person.