Computer Vision Engineer

Description:

1. Algorithm Development: Design, implement, and optimize computer vision algorithms, ensuring accuracy, efficiency, and scalability.

2. Data Processing and Preprocessing: Work with large datasets, and perform data cleaning, augmentation, and preprocessing to prepare it for training and evaluation.

3. Model Training and Evaluation: Utilize deep learning frameworks (e.g., TensorFlow, PyTorch) to train and evaluate computer vision models. Fine-tune pre-trained models for specific tasks.

4. Feature Extraction and Object Recognition: Develop techniques for feature extraction, object recognition, and semantic segmentation in visual data.

5. Real-time Processing: Implement real-time computer vision solutions for applications that require low-latency processing.

6. Hardware Optimization: Collaborate with hardware engineers to optimize algorithms for specific hardware platforms, ensuring efficient utilization of resources.

7. Integration and Deployment: Integrate computer vision solutions into existing systems and deploy them in production environments.

8. Documentation and Reporting: Maintain thorough documentation of algorithms, experiments, and results. Prepare reports and presentations for internal teams and stakeholders.

9. Stay Updated on Industry Trends: Stay abreast of the latest advancements in computer vision, machine learning, and related fields. Apply cutting-edge research to enhance our solutions.

Qualifications:

- Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related field.

- Strong proficiency in Python, and experience with popular computer vision libraries (OpenCV, Dlib, etc.).

- Strong proficiency in GANs ( Generative Adversarial Network Technology )

- In-depth knowledge of machine learning and deep learning techniques, particularly in the context of computer vision.

- Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar.

- Experience with GPU programming and parallel computing is a plus.

- Familiarity with cloud platforms (AWS, Azure, GCP) for deploying and scaling computer vision solutions.

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration abilities.