Junior AI Engineer

Role overview

Key responsibilities

• Develop and train computer vision models for image and video analysis.
• Implement object detection, image classification, segmentation, and tracking solutions.
• Prepare datasets through cleaning, labeling, and augmentation.
• Optimize models for GPU performance, inference speed, and scalability.
• Deploy AI models into production using APIs and containerized services.
• Integrate computer vision models with AI and analytics platforms.
• Collaborate with software engineers, data scientists, and product teams.
• Maintain documentation, code quality, and reproducibility.

Required skills and qualifications

• Minimum two years of hands-on AI, machine learning, or deep learning experience focused on computer vision.
• Master’s degree in computer science, software engineering, artificial intelligence, engineering, or a related field.
• Strong knowledge of computer vision concepts and algorithms.
• Practical experience with CNN-based models and modern computer vision architectures.
• Proficiency in Python, PyTorch or TensorFlow, and OpenCV.
• Experience with object detection and segmentation frameworks such as YOLO or Detectron2.
• Understanding of model evaluation, metrics, and performance optimization.
• Experience deploying models in cloud or on-premises environments.
• Familiarity with Docker and basic MLOps practices.
• Excellent written and spoken English communication skills.

Nice to have

• Experience with video analytics or real-time inference.
• Exposure to Vision Transformers or multimodal AI.
• Experience with GPU-based training and inference.
• Knowledge of OCI, AWS, Azure, or GCP.
• Background in healthcare, smart cities, or industrial AI.

What the employer offers

• Work on practical, production-grade computer vision solutions.
• Access to GPU infrastructure and modern AI tooling.
• Collaborative, engineering-focused work environment.
• Opportunities for growth and advanced AI exposure.
• Competitive compensation package.