Deep Learning / ML Engineer

Job Description : Deep Learning / ML Engineer

Key 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 techniques.

Apply machine learning algorithms for feature extraction, classification, detection, and prediction from complex signals.

Utilize image and signal processing methods to enhance model performance and data quality.

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.

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.

Proficiency in Python is essential; experience with libraries such as TensorFlow, PyTorch, NumPy, 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 processing and computer vision applications.

Education :

Ph.D degree in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, or a related field with a focus on deep learning.

Soft Skills :

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.