
Machine Learning and Computer Vision Professional
1 day ago
This position requires a strong background in machine learning and computer vision to design, develop, and deploy innovative solutions.
Key Responsibilities- Design and Develop Machine Learning Models: Create and optimize machine learning models for tasks such as object detection, image segmentation, and facial recognition.
- Implement Computer Vision Algorithms: Utilize frameworks such as OpenCV, TensorFlow, PyTorch, or similar to implement computer vision algorithms.
- Preprocess Large Datasets: Prepare and preprocess large datasets, including data augmentation and transformation techniques to enhance model performance.
- Evaluate Model Performance: Assess model performance using various metrics and techniques, including cross-validation, to ensure high accuracy and robustness.
- Deploy Models in Production Environments: Ensure scalability, efficiency, and reliability by deploying machine learning models in production environments.
- Cross-Functional Collaboration: Work closely with teams to integrate models into products and systems, providing technical support and troubleshooting as needed.
- Stay Up-to-Date with Advancements: Remain current with the latest developments in machine learning and computer vision, applying relevant findings to improve existing solutions.
- Maintain Comprehensive Documentation: Keep detailed records of models, algorithms, and processes to support ongoing maintenance and future development.
- Education: Bachelor's degree in Computer Science, Electrical Engineering, Data Science, or a related field. A Master's degree is a plus.
- Experience: At least 2 years of experience in machine learning and computer vision, with a proven track record of developing and deploying successful models.
- Technical Skills:
- Proficiency in Python and experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch.
- Strong understanding of computer vision techniques and libraries like OpenCV.
- Experience with deep learning techniques, including convolutional neural networks (CNNs) and transfer learning.
- Familiarity with cloud platforms and experience deploying models in production environments.
- Strong programming skills with a focus on clean, efficient, and well-documented code.
- Soft Skills:
- Strong problem-solving abilities and analytical thinking.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Ability to work independently as well as in a collaborative team environment.
- Strong organizational skills with attention to detail.
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