You will be part of a talented team of engineers and AI researchers focused on making our lives better and safer. As an AI engineer, you are responsible for building computer vision models that create extrinsic value for our clients.
This includes all associated areas such as machine learning, deep learning, computer vision, and also image processing.
JOB RESPONSIBILITIES
- Research and develop existing computer vision algorithms and incorporate novel techniques or create new algorithms from the ground up to solve desired use cases.
- Develop and adapt advanced computer vision and state-of-the-art deep learning techniques for face recognition, object segmentation/detection/classification / OCR.
- Prototype, benchmark, and implement new algorithms in production-level code.
- Deploy deep learning models into production.
- Assist the business team to deliver product value.
- Assist in testing and evaluation on the developed solutions by unit test, stress test, etc.
- Write professional documents for what you have developed.
JOB REQUIREMENTS
- Solid understanding of machine learning and deep learning is a must
- At least 1 years of R&D experience in the field of deep learning
- Experience with deep learning frameworks (Tensorflow, Pytorch).
- Hands on experience in computer vision algorithms such as segmentation, object classification, and object detection.
- Proficiency in C++ and/or Python, and OpenCV.
- Strong willingness to learn and grow.
- Self-learning ability, passionate, open-minded, team player, good communication skill, and able to work with minimal supervision effort.
- Ability to research, prototype, benchmark and implement new algorithms in production-level code.
- Bachelor's degree in Computer Science / Information Technology / Engineering / Mathematics or related fields.
BONUS POINTS
- Proficiency in data analysis skills to facilitate decision-making
- Real-world CV projects in the role of CV developer with algorithm implementation.
- Strong background in computer vision and image processing.
- Experience in model optimization, knowledge distillation, and deployment on edge and mobile devices.
- Experience with Docker and deployment
- Experience with Linux architecture and familiar with Linux command.
- Experience in using source control/project tracking systems such as GitHub, Jira, etc.
- Experience with Docker and frameworks such as Flask and FastAPI.
- M.S. or Ph.D in computer vision or related field.
- Contributions to open-source projects.
- Active participant in technical communities.
