Machine Learning Developer

Description

Job Summary: Join us to revolutionize electronic security with AI in a dynamic and creative environment, developing cutting-edge solutions in Video Management Systems (VMS) and AI for cameras. Key Highlights: 1. Revolutionize the future of electronic security with AI 2. A dynamic, creative environment with freedom to innovate 3. Develop cutting-edge solutions in VMS and AI Come revolutionize the future of electronic security with AI! EMIVE\&CO, with 30 years of innovation in electronic security solutions, is undergoing rapid expansion and developing high-end applications leveraging artificial intelligence, backed by extensive expertise accumulated throughout its history in security. We are seeking a Junior/Mid-level Machine Learning Engineer to join our team of experts and create cutting-edge solutions in Video Management Systems (VMS) and other AI applications within the context of cameras and security. If you wish to be part of a dynamic, creative environment that offers freedom to innovate, this opportunity is for you! **Key Responsibilities:** Develop and implement machine learning models focused on electronic security, such as anomaly detection, event detection, and suspicious behavior identification.Collaborate on the design and development of machine learning pipelines on cloud computing platforms (AWS, Azure, Google Cloud), optimizing costs and enabling model scalability.Be responsible for selecting and maintaining algorithms serving as the foundation for building artificial intelligence solutions.Propose improvements to algorithms and infrastructure aimed at reducing costs and/or enhancing technical performance.Present state-of-the-art AI-based solutions, considering the target market of electronic security and monitoring.Develop and maintain machine learning APIs and services integrated with monitoring and security systems.Perform model training and parameter tuning to ensure accuracy and efficiency of production solutions.Integrate supervised and unsupervised learning techniques—for example, to optimize automatic event detection in surveillance systems.Collaborate with multidisciplinary teams to implement robust and scalable cloud-based solutions.Propose and apply best practices in MLOps for AI model deployment and monitoring.Technically contribute to the machine learning development team. **Technical Requirements:** Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related fields.Practical experience in developing and implementing machine learning models and AI-powered solutions (minimum 2 years).Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit\-learn.Understanding of supervised and unsupervised learning algorithms.Teamwork skills and ability to collaborate across different project areas.Strong communication skills to discuss progress and results of implemented models.Experience with cloud computing platforms (AWS, Azure, Google Cloud) and integration with machine learning services.Advantageous qualifications include: In-depth knowledge of computer vision, including convolutional neural networks (CNNs) and object detection techniques in images and videos.Relevant postgraduate degree in data science or Machine Learning.Experience with surveillance systems and electronic security solutions.Knowledge of cameras and video streaming protocols (RTSP, RTMP, HLS, and proprietary protocols);Certifications and training in cloud computing or machine learning.Experience optimizing models for deployment in cloud or edge computing environments. **Behavioral Profile:** Active learning.Innovation.Collaboration.Time management. **Minimum Education Level:** High School (Secondary Education)