Machine Learning Developer

Description

Job Summary: Join us to revolutionize electronic security with AI and become part of a dynamic team developing cutting-edge solutions in Video Management Systems (VMS) and AI applications. Key Highlights: 1. Revolutionize electronic security with AI 2. A dynamic, creative environment with freedom to innovate 3. Develop cutting-edge VMS and AI solutions for security Come revolutionize the future of electronic security with AI! EMIVE\&CO, with 30 years of innovation in electronic security solutions, is expanding rapidly 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 specialists and build cutting-edge solutions in Video Management Systems (VMS) and other AI applications within camera and security contexts. If you seek a dynamic, creative environment that offers freedom to innovate, this opportunity is for you! **Key Responsibilities:** Develop and implement machine learning models tailored for 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.Select and maintain algorithms serving as the foundation for building AI solutions.Propose algorithmic and environmental improvements aimed at cost reduction and/or technical enhancements.Present state-of-the-art AI-based solutions aligned with the electronic security and monitoring market.Develop and maintain machine learning APIs and services integrated with monitoring and security systems.Train models and tune parameters to ensure accuracy and efficiency of production-ready solutions.Integrate supervised and unsupervised learning techniques — for example, to optimize automatic event detection in surveillance systems.Collaborate with cross-functional teams to implement robust and scalable cloud-based solutions.Propose and apply MLOps best practices for AI model deployment and monitoring.Technically contribute to the Machine Learning developer team for product development. **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 project domains.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, such as 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);Cloud computing or machine learning certifications and training.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)