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oracle

AI Engineer

Space42
Abu Dhabi, UAE
Full-time
Mid
Onsite
Discovered 2 weeks ago
PythonTensorFlowPyTorchAWSAzureGoogle Cloud
Free

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PythonTensorFlowPyTorch
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Responsibilities

  • AI Model Development: Design, develop and deploy to production state-of-the-art AI models across multiple domains, including natural language processing, computer vision, recommendation systems, and more.
  • Data Preprocessing: Clean, preprocess, and analyze and augment data to prepare it for model training and evaluation.
  • Model Training: Train and fine-tune AI models using cutting-edge techniques and libraries, ensuring high performance and accuracy.
  • Validation and Testing: Conduct rigorous testing and validation of AI models to ensure robustness, reliability, and generalization.
  • Optimization: Optimize models for performance, speed, and scalability, taking into account resource constraints.
  • Collaboration: Collaborate closely with cross-functional teams, including data scientists, software engineers, and domain experts and stakeholders to integrate AI solutions into products and services.
  • Research and Innovation: Stay up-to-date with the latest advancements in AI research and apply them to solve real-world problems effectively.
  • Documentation: Create clear and concise documentation for AI models, algorithms, and processes to facilitate knowledge sharing and future development.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. Ph.D. is a plus.
  • Experience in developing and deploying AI models
  • Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar.
  • Deep understanding of machine learning algorithms, deep learning frameworks, and AI technologies.
  • Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.
  • Excellent communication skills to convey complex technical concepts to both technical and non-technical stakeholders.
  • Ideally, you’ll also need:
  • Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud).
  • Knowledge of ML Ops practices for AI model deployment and maintenance.
  • Familiarity with big data technologies and distributed computing.
  • Published research or contributions to the AI community.

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