AI/ML Engineer

About the job

About MostEdge MostEdge empowers retailers with smart, trusted, and sustainable solutions to run their stores more efficiently. Through our Inventory Management Service, powered by the StockUPC app, we provide accurate, real-time insights that help stores track inventory, prevent shrink, and make smarter buying decisions. Our mission is to deliver trusted, profitable experiences—empowering retailers, partners and employees to accelerate commerce in a sustainable manner. Job Summary: We are seeking a highly skilled and motivated AI/ML Engineer with a specialization in Computer Vision & Un-Supervised Learning to join our growing team. You will be responsible for building, optimizing, and deploying advanced video analytics solutions for smart surveillance applications, including real-time detection, facial recognition, and activity analysis. This role combines the core competencies of AI/ML modelling with the practical skills required to deploy and scale models in real-world production environments, both in the cloud and on edge devices. Key Responsibilities: - AI/ML Development & Computer Vision • Design, train, and evaluate models for: • Face detection and recognition • Object/person detection and tracking • Intrusion and anomaly detection • Human activity or pose recognition/estimation • Work with models such as YOLOv8, DeepSORT, RetinaNet, Faster-RCNN, and InsightFace. • Perform data preprocessing, augmentation, and annotation using tools like LabelImg, CVAT, or custom pipelines. - Surveillance System Integration • Integrate computer vision models with live CCTV/RTSP streams for real-time analytics. • Develop components for motion detection, zone-based event alerts, person re-identification, and multi-camera coordination. • Optimize solutions for low-latency inference on edge devices (Jetson Nano, Xavier, Intel Movidius, Coral TPU). - Model Optimization & Deployment • Convert and optimize trained models using ONNX, TensorRT, or OpenVINO for real-time inference. • Build and deploy APIs using FastAPI, Flask, or TorchServe. • Package applications using Docker and orchestrate deployments with Kubernetes. • Automate model deployment workflows using CI/CD pipelines (GitHub Actions, Jenkins). • Monitor model performance in production using Prometheus, Grafana, and log management tools. • Manage model versioning, rollback strategies, and experiment tracking using MLflow or DVC. - Collaboration & Documentation • Work closely with backend developers, hardware engineers, and DevOps teams. • Maintain clear documentation of ML pipelines, training results, and deployment practices. • Stay current with emerging research and innovations in AI vision and MLOps.

Requirements

• Computer Vision
• AI/ML Development
• Deep Learning
• Real-time Analytics
• Model Deployment

Qualifications

• Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or a related field
• 3–6 years of experience in AI/ML, with a strong portfolio in computer vision, Machine Learning.

Preferred Technologies

• Computer Vision
• AI/ML Development
• Deep Learning
• Real-time Analytics
• Model Deployment