Design, develop, and implement deep learning models for computer vision, image processing, and signal processing applications, and optimize them for deployment on edge devices.
Requirements
- 2–5 years of hands-on experience developing and optimizing machine learning models and algorithms, with an emphasis on computer vision, image processing, and signal processing.
- Strong proficiency in Python; experience with libraries such as TensorFlow, PyTorch, NumPy, SciPy, and OpenCV is highly desirable.
- Solid understanding of software development practices including version control (e.g., Git), testing, and continuous integration.
- Proven experience with performance optimization techniques for ML models, especially in edge-computing environments.
- Strong background in machine learning and deep learning, particularly in signal and image processing applications.
Responsibilities
- Design, develop, and implement deep learning models using architectures such as CNNs, RNNs, and GANs, with a focus on state-of-the-art computer vision, image processing, and signal processing techniques.
- Apply machine learning algorithms for feature extraction, classification, detection, and prediction from complex image and signal data.
- Utilize advanced image and signal processing methods to enhance model performance, data quality, and system robustness.
- Optimize machine learning models for deployment on edge devices, ensuring efficient use of limited computational resources.
- Collaborate with cross-functional teams to integrate ML solutions into production systems.
- Write clean, efficient, and well-documented Python code following best software development practices.
Other
- Ph.D. degree in Computer Science, Robotics, Electrical Engineering, Computer Engineering, Mathematics, or a related field with a focus on deep learning, computer vision, or signal/image processing.
- Strong analytical and problem-solving skills with a keen attention to detail.
- Excellent communication and collaboration skills to work effectively with interdisciplinary teams and stakeholders.
- Highly organized, self-motivated, and capable of managing multiple priorities in a fast-paced environment.
