Computer Vision Engineer
1 month ago
Job Overview :
We are seeking a talented and motivated Computer Vision Engineer with 5+ years of experience to join our team. The ideal candidate will have hands-on experience in building and deploying computer vision models and applications.
You will work on cutting-edge technologies, solving complex problems related to image processing, object detection, recognition, and video analysis. This role involves close collaboration with data scientists, machine learning engineers, and software developers to bring advanced computer vision solutions to production.
Key Responsibilities :
- Design, develop, and implement computer vision algorithms for tasks such as object detection, image classification, facial recognition, and video analysis.
- Develop and optimize deep learning models for image and video processing using frameworks like TensorFlow, PyTorch, or OpenCV.
- Preprocess large-scale datasets including images and videos to build high-performance computer vision models.
- Deploy computer vision models into production, ensuring scalability, performance, and reliability.
- Collaborate with cross-functional teams to integrate computer vision solutions with existing systems.
- Stay up to date with the latest research and advancements in computer vision and related fields.
- Optimize algorithms for real-time processing on edge devices or cloud environments.
- Perform testing and validation of computer vision models to ensure high accuracy and robustness.
- Work with software engineering teams to build and maintain computer vision pipelines.
- Debug and troubleshoot issues in the model's performance or system integration.
Required Skills and Qualifications :
- 4-5 years of experience in computer vision, image processing, and deep learning.
- Strong proficiency in programming languages like Python and experience with computer vision libraries such as OpenCV or PIL.
- Hands-on experience with deep learning frameworks like TensorFlow, Keras, or PyTorch.
- Solid understanding of image processing techniques (e.g., filtering, feature extraction, edge detection).
- Experience with algorithms for object detection, segmentation, image classification, or video tracking.
- Familiarity with machine learning pipelines and tools (e.g., Scikit-learn, Pandas).
- Experience working with large-scale image and video datasets.
- Strong understanding of neural networks, convolutional neural networks (CNNs), and transfer learning.
- Knowledge of cloud platforms like AWS, Azure, or GCP for deploying models.
- Proficient with version control systems (Git) and collaborative development workflows.
- Strong analytical and problem-solving skills.
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