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.

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· 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.