Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions.
Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most.
Job Responsibilities
- Assist in developing and optimizing AI / machine learning models for real-world applications
- Train, evaluate, and improve model performance using structured datasets
- Support experimentation and implementation of deep learning techniques (e.g. CV, NLP)
- Collaborate with engineering teams to integrate AI models into products
- Stay updated with latest AI/ML developments and contribute ideas to projects
Job Requirements
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or related field (Master’s is a plus)
- Strong foundation in machine learning, data structures, and algorithms
- Familiarity with deep learning frameworks (e.g. TensorFlow or PyTorch)
- Basic understanding of computer vision or NLP concepts
- Strong problem-solving skills and ability to learn independently
- Good teamwork and communication skills
Nice to Have
- Exposure to Transformers, Vision Transformers (ViT), or multimodal models (VLMs)
- Experience with AI/ML projects, internships, or competitions
- Familiarity with model training, tuning, and evaluation techniques
- Knowledge of deploying ML models (APIs, cloud, etc.)
Why Join Us
- Kickstart Your Engineering Career
Gain hands-on experience, with guidance from experienced engineers.
- Structured Learning & Mentorship
Learn best practices
- Regional Exposure.
Collaborate with local and regional teams, gaining valuable experience working in a cross-border environment.
- Growth & Career Development
Clear progression path with opportunities to grow.
- Supportive Team Culture
Work in a collaborative environment where knowledge sharing and continuous improvement are encouraged.