AI Staffing Ninja
Location
Gurgaon | India
Job description
Responsibilities: Design and develop deep learning models and algorithms for various applications, such as computer vision, natural language processing, and speech recognition. Collect, preprocess, and analyze large-scale datasets to train deep neural networks. Implement and optimize deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models. Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to define project requirements and objectives. Stay up-to-date with the latest advancements in deep learning research and technologies, and apply them to enhance model performance. Conduct experiments and perform rigorous testing to evaluate and improve the accuracy and efficiency of deep learning models. Optimize and fine-tune deep learning models for deployment in production systems, considering factors such as computational resources and real-time constraints. Write clean, efficient, and maintainable code in languages such as Python, and utilize deep learning libraries and frameworks like TensorFlow, PyTorch, or Keras. Apply techniques like transfer learning, data augmentation, and regularization to improve model generalization and reduce overfitting. Collaborate with the data engineering team to ensure data pipelines and infrastructure support efficient training and deployment of deep learning models. Document and communicate research findings, methodologies, and best practices to stakeholders and team members. Mentor and provide guidance to junior team members, and contribute to the continuous learning and development of the deep learning team.
Requirements: Bachelor's or Master's degree in computer science, electrical engineering, or a related field. A Ph.D. is a plus. Solid understanding of machine learning principles and algorithms, particularly deep learning techniques. Proficiency in programming languages such as Python, with experience in using deep learning frameworks (e.g., TensorFlow, PyTorch, Keras). Experience in developing and training deep neural networks for various tasks, such as image classification, object detection, sequence modeling, or natural language understanding. Strong knowledge of linear algebra, calculus, probability, and statistics, and their application in deep learning. Familiarity with data preprocessing, feature engineering, and data visualization techniques. Hands-on experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and distributed computing frameworks (e.g., TensorFlow Distributed, Horovod) is preferred. Strong problem-solving skills and the ability to think critically and creatively in developing innovative deep learning solutions. Excellent communication and teamwork skills, with the ability to collaborate effectively with both technical and non-technical stakeholders. A strong portfolio or track record of deep learning projects, research publications, or contributions to the deep learning community is a plus.Job tags
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