Job Description
Job Description
Job Description: Deep Learning / ML Engineer
Key Responsibilities:
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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 techniques.
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Apply machine learning algorithms for feature extraction, classification, detection, and prediction from complex signals.
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Utilize image and signal processing methods to enhance model performance and data quality.
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Optimize machine learning models for deployment on edge devices, ensuring efficient use of limited computational resources.
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Collaborate with cross-functional teams to integrate ML solutions into production systems.
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Write clean, efficient, and well-documented Python code following best software development practices.
Required Qualifications:
- 2-5 years of hands-on experience optimizing machine learning models and algorithms for deployment on edge devices, with an emphasis on computational efficiency and resource constraints.
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Proficiency in Python is essential; experience with libraries such as TensorFlow, PyTorch, NumPy, and OpenCV is highly desirable.
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Solid understanding of software development practices including version control (e.g., Git), testing, and continuous integration.
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Proven experience with performance optimization techniques for ML models, especially in edge-computing environments.
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Strong background in machine learning and deep learning, particularly in signal processing and computer vision applications.
Education:
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Master's degree in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, or a related field with a focus on deep learning.
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Ph.D. preferred.
Soft Skills:
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Strong analytical and problem-solving skills with a keen attention to detail.
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Excellent communication and collaboration skills to work effectively with interdisciplinary teams and stakeholders.
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Highly organized, self-motivated, and capable of managing multiple priorities in a fast-paced environment.