Junior AI Engineer - Computer Vision

As a Junior Computer Vision Engineer at InnovationTeam, you will be responsible for designing, developing, and deploying vision-based AI systems for real-world, production environments. You will work closely with cross-functional teams to build scalable image and video analytics solutions.

This position requires strong expertise in computer vision, deep learning, and software engineering. The ideal candidate is technically strong, self-driven, and experienced in taking AI models from research to production.

At InnovationTeam, we foster a culture of innovation, collaboration, and technical excellence, offering an environment where Junior engineers can make a meaningful impact., We are seeking a skilled AI Engineer with a strong focus on Computer Vision to develop, optimize, and deploy vision-based AI solutions. The role involves working on real-world image and video analytics problems and delivering production-ready AI systems. Requirements * Develop and train Computer Vision models for image and video analysis.

• Implement solutions for object detection, image classification, segmentation, and tracking.
• Prepare and manage datasets, including data cleaning, labelling, 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 broader AI and analytics platforms.
• Collaborate with software engineers, data scientists, and product teams.
• Maintain documentation and ensure code quality and reproducibility.

Do you have a Master’s degree?, * Minimum 5 years of hands-on experience in AI / Machine Learning/Deep learning with a focus 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 CV architectures.
• Proficiency in Python and common ML/CV libraries (PyTorch or TensorFlow, OpenCV).
• Experience with object detection and segmentation frameworks (e.g., YOLO, Detectron2).
• Understanding of model evaluation, metrics, and performance optimization.
• Experience deploying models in cloud or on-prem environments.
• Familiarity with Docker and basic MLOps practices.
• Excellent English communication skills (written and spoken).

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 cloud platforms (OCI, AWS, Azure, or GCP).
• Background in domains such as healthcare, smart cities, or industrial AI.

* 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.