At Aristocrat, We are on a mission to find the best talent potential individuals in thirst for innovation & Knowledge evolution.
Career in Aristocrat Involves remote modality and several cutting edge stipend linked corporate certification in house programs.
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The Neural Network Engineer will be responsible for designing and developing neural networks and deep learning models to solve complex problems in various fields. The engineer will work with a team of data scientists, software engineers, and stakeholders to identify opportunities for neural network applications, and will collaborate to design, develop, and deploy solutions. The position may involve working on multiple projects simultaneously, and may require some level of creativity and innovation in neural network development.
Responsibilities:
- Collaborate with stakeholders to identify opportunities for neural network applications and develop solutions to solve complex problems.
- Design and develop neural networks and deep learning models, including data preprocessing, model architecture, model training, and evaluation.
- Optimize and fine-tune neural network models to improve performance and efficiency.
- Work with a team of data scientists, software engineers, and stakeholders to integrate neural network solutions into software systems and ensure successful deployment.
- Analyze and interpret data to evaluate neural network performance and identify areas for improvement.
- Stay current on trends and advancements in neural networks and related technologies.
Requirements
- Bachelors degree or higher in Computer Science, Mathematics, or a related field.
- Strong programming skills in languages such as Python, Java, or C++.
- Experience in neural network development, with a focus on deep learning and related techniques such as convolutional neural networks, recurrent neural networks, or generative adversarial networks.
- Familiarity with deep learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.
- Knowledge of statistics, linear algebra, and probability theory.
- Experience with data preprocessing, model architecture, model training, and evaluation.
- Familiarity with software development tools and methodologies.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork skills.
Benefits
Extreme Learning and training environment.
Continuous growth every 3 months financially & in Responsibilities.
Compensation based on contribution value.
Neural Network, Deep Learning, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, TensorFlow, PyTorch, Keras, Statistics, Linear Algebra, Probability Theory, Data Preprocessing