Ai Ml Engineer

Role Overview:

We are seeking an accomplished AI/ML Engineer with deep expertise in designing, deploying, and optimizing scalable AI solutions in cloud environments. The ideal candidate will have a proven track record in real-time object detection, video analytics, and cloud-native ML systems, with a focus on Microsoft Azure and advanced ML frameworks. This role requires strong technical leadership, hands-on development skills, and the ability to drive innovation in a fast-evolving technology landscape.

Key Responsibilities

• Architect, develop, and deploy robust machine learning models for real-time object detection and video analytics, leveraging frameworks such as YOLO, TensorFlow, and PyTorch.
• Design and implement scalable, secure, and highly available cloud services using Microsoft Azure, AzureML, and Azure Kubernetes Service.
• Ingest and process real-time video streams via RTSP protocols, extracting actionable insights for mission-critical applications.
• Perform Custom Object detection, tracking, counting, zone intrusion, etc tasks using OpenCV and YOLO models.
• Lead the end-to-end ML lifecycle: data engineering, model development, training, fine tuning, optimization, and production deployment.
• Build and maintain microservices in Linux/Kubernetes environments, utilizing containerization technologies (Docker, Kubernetes) and open-source tools.
• Develop and automate CI/CD pipelines, manage version control (Git, DVC), and enforce rigorous code quality standards.
• Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to deliver impactful, production-grade solutions.
• Monitor, troubleshoot, and optimize system performance, ensuring high availability, reliability, and scalability.
• Stay current with advancements in AI/ML, cloud computing, and software engineering best practices, proactively integrating emerging technologies into solutions.

Technical Skills:

• Expert in Python and ML frameworks: YOLO, TensorFlow, PyTorch, OpenAI APIs.
• Proficient in Java; familiarity with C++ is advantageous.
• Deep understanding of supervised/unsupervised learning, deep learning architectures, and transformer models.
• Hands-on with container orchestration (Docker, Kubernetes), RESTful APIs, and microservices architecture.
• Strong background in data structures, algorithms, and software design principles.
• Experience with real-time data processing and streaming technologies.