AI/Deep Learning Engineer
5 days ago
Job Overview:
We are seeking an AI/Deep Learning Engineer to join our team and help us build cutting-edge machine learning models and algorithms that solve complex business problems. The ideal candidate will have a strong foundation in AI, deep learning, and machine learning algorithms with experience in building, training, and deploying deep learning models. This role will work closely with cross-functional teams to implement AI solutions in both production and research environments.
Key Responsibilities:
· Design and Build Models: Develop, implement, and optimize deep learning models using frameworks such as TensorFlow, PyTorch, and Keras.
· Data Processing and Management: Work with large datasets, clean, preprocess, and transform data for use in training deep learning models.
· Algorithm Development: Research and develop new algorithms for various applications including computer vision, natural language processing (NLP), reinforcement learning, and more.
· Model Training and Tuning: Train models using GPUs/TPUs, optimize them, and fine-tune them to improve performance.
· Deployment: Deploy models in production environments, ensuring that they meet performance and scalability requirements.
· Collaboration: Collaborate with data engineers, software engineers, and product teams to integrate AI solutions into products and services.
· Stay Updated: Continuously research and stay up-to-date with the latest trends and advancements in deep learning and AI.
Documentation: Create and maintain thorough documentation for models, data pipelines, and systems.
Requirements
Required Skills and Qualifications:
· Education: Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
· Experience: Minimum of 3-5 years of professional experience in machine learning or deep learning roles.
· Technical Skills:
o Expertise in Deep Learning frameworks like TensorFlow, Keras, PyTorch.
o Strong understanding of neural networks, backpropagation, convolutional networks (CNNs), recurrent neural networks (RNNs), transformers, and GANs.
o Solid understanding of machine learning concepts and algorithms.
o Strong proficiency in Python, including libraries like NumPy, Pandas, SciPy, Scikit-learn, and Matplotlib.
o Experience with GPU/TPU programming for efficient training.
o Knowledge of cloud platforms such as AWS, Azure, or Google Cloud for model deployment.
o Familiarity with containerization (Docker) and CI/CD pipelines for model deployment.
o Experience in working with NLP, Computer Vision, or Reinforcement Learning projects is a plus
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