AI ML Engineer

Role & Responsibilities

·        4+ years of experience applying AI to practical uses

·        Develop and train computer vision models for tasks like:

·        Object detection and tracking (YOLO, Faster R-CNN, etc.)

·        Image classification, segmentation, OCR (e.g., PaddleOCR, Tesseract)

·        Face recognition/blurring, anomaly detection, etc.

·        Optimize models for performance on edge devices (e.g., NVIDIA Jetson, OpenVINO, TensorRT).

·        Process and annotate image/video datasets; apply data augmentation techniques.

·        Proficiency in Large Language Models.

·        Strong understanding of statistical analysis and machine learning algorithms.

·        Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.

·        Understanding of image processing concepts (thresholding, contour detection, transformations, etc.)

·        Experience in model optimization, quantization, or deploying to edge (Jetson Nano/Xavier, Coral, etc.)

·        Strong programming skills in Python (or C++), with expertise in:

·        Implement and optimize machine learning pipelines and workflows for seamless integration into production systems.

·        Hands-on experience with at least one real-time CV application (e.g., surveillance, retail analytics, industrial inspection, AR/VR).

·        OpenCV, NumPy, PyTorch/TensorFlow

·        Computer vision models like YOLOv5/v8, Mask R-CNN, DeepSORT

·        Engage with multiple teams and contribute on key decisions.

·        Expected to provide solutions to problems that apply across multiple teams.

·        Lead the implementation of large language models in AI applications.

·        Research and apply cutting-edge AI techniques to enhance system performance.

·        Contribute to the development and deployment of AI solutions across various domains