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4 days ago
We are seeking a highly skilled Machine Learning and Computer Vision Engineer to join our dynamic team at AHOY. In this role, you will be responsible for developing and deploying machine learning models and computer vision algorithms that solve complex real-world problems.
Responsibilities- Develop Machine Learning Models: Design, develop, and optimize machine learning models, particularly in the field of computer vision, for tasks such as object detection, image segmentation, and facial recognition.
- Implement Computer Vision Algorithms: Implement computer vision algorithms using frameworks such as OpenCV, TensorFlow, PyTorch, or similar.
- Analyze and Process Data: Prepare and preprocess large datasets, including data augmentation and transformation techniques to enhance model performance.
- Evaluate Model Performance: Evaluate model performance using various metrics and techniques, including cross-validation, to ensure high accuracy and robustness.
- Deploy Models in Production Environments: Deploy machine learning models in production environments, ensuring they are scalable, efficient, and reliable.
- Collaborate with Cross-Functional Teams: Work closely with cross-functional teams to integrate models into products and systems, providing technical support and troubleshooting as needed.
- Stay Up-to-Date with Industry Advancements: Stay up-to-date with the latest advancements in machine learning and computer vision, and apply relevant findings to improve existing solutions.
- Maintain Clear Documentation: Maintain clear and comprehensive documentation 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 3 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 (e.g., AWS, Azure, Google Cloud) 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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