Machine Learning Engineer / Computer Vision Expert
Role Overview
We are looking for a Machine Learning Engineer / Computer Vision Expert who is proficient in developing, training, and optimizing object detection and image recognition models . The ideal candidate will have strong expertise in deep learning frameworks and practical experience deploying models for production use.
You’ll be working on exciting projects involving real-time video analytics, automated visual inspection, and intelligent image processing pipelines .
Key Responsibilities
- Design, develop, and deploy object detection and image classification models using state-of-the-art deep learning techniques.
- Perform data preprocessing, augmentation, and annotation to improve model performance.
- Train, fine-tune, and evaluate models using frameworks such as TensorFlow, PyTorch, or OpenCV .
- Work with datasets from various sensors and camera systems , ensuring scalability and robustness.
- Develop automated training pipelines and maintain reproducible experiments.
- Collaborate with backend and frontend teams to integrate AI models into production environments.
- Research and experiment with emerging trends in Computer Vision such as YOLOv8, DETR, Segment Anything, and Vision Transformers (ViT).
- Prepare technical documentation , maintain version control, and ensure best practices in ML lifecycle management.
Required Skills and Qualifications
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.3–5 years of hands-on experience in Computer Vision and Machine Learning.Strong proficiency in Python and libraries such as NumPy, Pandas, and Scikit-learn.Expertise in deep learning frameworks : TensorFlow, PyTorch, or Keras.Solid experience with object detection architectures (YOLO, Faster R-CNN, SSD, Mask R-CNN, etc.).Experience with image and video processing tools (OpenCV, Pillow, etc.).Understanding of data annotation tools and dataset management pipelines .Familiarity with MLOps tools (MLflow, DVC, Docker, etc.) is a plus.Experience deploying models on cloud platforms (AWS, Azure, or GCP) is preferred.Strong analytical, problem-solving, and communication skills.Preferred Qualifications
Experience with Edge AI and deploying models on embedded systems or mobile devices.Familiarity with real-time video processing and streaming data pipelines .Contribution to open-source computer vision projects or research publications.#J-18808-Ljbffr