Junior AI Engineer - Computer Vision

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.

Role Overview

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.

Key Responsibilities

·       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.

Required Skills & Qualifications

·       Minimum 2 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.

What We Offer

·       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.