Python Developer

Role Overview: As a Computer Vision and Deep Learning Engineer, your main responsibility will be to apply your expertise in computer vision and deep learning algorithms to develop innovative solutions for object detection, tracking, and image segmentation. You will be expected to have a strong understanding of machine learning frameworks such as Tensorflow, Keras, Scikit-Learn, and PyTorch. Additionally, you should be proficient in training models using GPU computing and possess the ability to implement research findings into practical solutions for real-world problems. Your role will also involve utilizing image processing algorithms for feature engineering and demonstrating strong programming skills in Python. Key Responsibilities: - Demonstrate expertise in computer vision and deep learning algorithms for object detection, tracking, and image segmentation. - Utilize machine learning frameworks such as Tensorflow, Keras, Scikit-Learn, and PyTorch for model development. - Train models using GPU computing with NVIDIA CUDA or on cloud platforms. - Implement research findings into practical solutions for real-world applications. - Apply basic and advanced image processing algorithms for feature engineering. - Utilize Python and related packages for efficient coding and data manipulation. - Communicate effectively with team members and present technical information to diverse audiences. - Independently develop solutions in an organized manner and collaborate effectively in team settings. - Demonstrate strong Object-Oriented Programming and logical analysis skills in Python. Qualifications Required: - Minimum of 2 years of experience in computer vision and deep learning. - Proficiency in machine learning frameworks such as Tensorflow, Keras, Scikit-Learn, and PyTorch. - Experience with GPU computing using NVIDIA CUDA or cloud platforms. - Strong programming skills in Python and familiarity with related packages. - Excellent written and verbal communication skills. - Ability to work independently and collaboratively in a team environment. - Strong Object-Oriented Programming and logical analysis skills in Python. Role Overview: As a Computer Vision and Deep Learning Engineer, your main responsibility will be to apply your expertise in computer vision and deep learning algorithms to develop innovative solutions for object detection, tracking, and image segmentation. You will be expected to have a strong understanding of machine learning frameworks such as Tensorflow, Keras, Scikit-Learn, and PyTorch. Additionally, you should be proficient in training models using GPU computing and possess the ability to implement research findings into practical solutions for real-world problems. Your role will also involve utilizing image processing algorithms for feature engineering and demonstrating strong programming skills in Python. Key Responsibilities: - Demonstrate expertise in computer vision and deep learning algorithms for object detection, tracking, and image segmentation. - Utilize machine learning frameworks such as Tensorflow, Keras, Scikit-Learn, and PyTorch for model development. - Train models using GPU computing with NVIDIA CUDA or on cloud platforms. - Implement research findings into practical solutions for real-world applications. - Apply basic and advanced image processing algorithms for feature engineering. - Utilize Python and related packages for efficient coding and data manipulation. - Communicate effectively with team members and present technical information to diverse audiences. - Independently develop solutions in an organized manner and collaborate effectively in team settings. - Demonstrate strong Object-Oriented Programming and logical analysis skills in Python. Qualifications Required: - Minimum of 2 years of experience in computer vision and deep learning. - Proficiency in machine learning frameworks such as Tensorflow, Keras, Scikit-Learn, and PyTorch. - Experience with GPU computing using NVIDIA CUDA or cloud platforms. - Strong programming skills in Python and familiarity with related packages. - Excellent written and verbal communication skills. - Ability to work independently and collaboratively in a team environment. - Strong Object-Oriented Programming and logical analysis skills in Python.