Machine Learning Engineer

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Company Overview:

We are a dynamic and innovative system integration company based in India, specializing in advanced embedded systems and AI-driven vision solutions. Our projects span diverse industries and involve cutting-edge technologies like OpenCV, deep learning, and embedded platforms such as Raspberry Pi and NVIDIA Jetson. We focus on real-world applications including ANPR (Automatic Number Plate Recognition), UVSS (Under Vehicle Scanning Systems), and custom camera-based intelligent systems.

Position Overview:

We are seeking a skilled Machine Learning Engineer with hands-on experience in computer vision, camera-based systems, and embedded AI solutions. The ideal candidate will design and implement intelligent vision systems that power real-world automation and surveillance applications. This is an exciting opportunity to contribute to the development of scalable, reliable, and high-performance AI systems in a fast-paced and collaborative environment.

Key Responsibilities:

·     Design and develop camera-based ML solutions such as ANPR, UVSS, face detection/recognition, and motion tracking systems.

·     Implement and optimize computer vision algorithms using OpenCV, deep learning models (YOLO, SSD, etc.), and classical vision techniques.

·     Integrate ML models into embedded platforms like Raspberry Pi, NVIDIA Jetson, or similar ARM-based systems.

·     Calibrate and manage camera hardware (USB/IP cameras, IR/thermal, industrial cameras) and tune imaging pipelines for real-time applications.

·     Collaborate with hardware and software teams to develop end-to-end solutions from model training to edge deployment.

·     Perform system integration, testing, and performance benchmarking in real-world environments.

·     Continuously research and stay up to date on the latest in computer vision, ML frameworks, and edge AI deployments.

Requirements:

·     Bachelor’s degree in Computer Science, Electronics, Electrical Engineering, or a related field.

·     2+ years of experience in developing and deploying ML/Computer Vision solutions, preferably with a focus on camera-based applications.

·     Proficiency in Python and experience with OpenCV, NumPy, and related image processing libraries.

·     Experience with deep learning frameworks such as TensorFlow, PyTorch, ONNX.

·     Solid understanding of camera interfaces (USB, CSI, IP), camera calibration, and lens distortion correction.

·     Experience deploying ML models to edge devices (Raspberry Pi, NVIDIA Jetson, etc.) with performance optimization.

·     Familiarity with video streaming, RTSP, GStreamer, or similar media handling technologies.

·     Working knowledge of Git, Agile development practices, and CI/CD pipelines.

Preferred Qualifications:

·     Experience with real-time object detection, OCR (for number plate reading), vehicle classification, or motion analysis.

·     Understanding of embedded Linux systems and scripting (Bash, systemd, etc.).

·     Strong debugging skills for ML pipeline bottlenecks.

·     Prior experience in system deployment in transport, security, or industrial automation domains.