AI Engineer

1 week ago


Dubai, Dubai, United Arab Emirates Dice Full time
Responsibilities:
  • Develop and implement various generative AI models, such as LLMs, text-to-image, and others
  • Train and evaluate models using large datasets
  • Troubleshoot and debug code to ensure high-quality results
  • Stay updated with the latest advancements in generative AI
  • Scale models efficiently and understand their limitations
  • Identify opportunities for model enhancement
  • Utilize predictive modeling to optimize customer experiences and business outcomes
  • Collaborate with different teams for model implementation and monitoring
  • Develop processes and tools to analyze model performance and data accuracy
  • Lead data experiments and engage with stakeholders to drive data-driven solutions
  • Conduct advanced data analysis and design complex algorithmic models
  • Communicate quantitative analysis clearly and effectively
Requirements:
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • 2+ years of experience in developing and training AI/ML models
  • Proficiency in SQL, Python, and statistical/mathematical software
  • Knowledge of state-of-the-art generative AI models like GPT-3, DALL-E, and CLIP
  • Experience with Cloud infrastructure and Platforms (Azure, Google Cloud Platform, AWS)
  • Working knowledge of Kore.AI and Prompt Engineering
  • Experience in training and evaluating large-scale models on high-performance computing clusters
  • Strong understanding of deep learning, NLP, and computer vision
  • Excellent problem-solving skills and ability to work independently and in a team
Preferred Qualifications:
  • Bachelor's or Master's degree in computer science, Data Science, Statistics, Math, Physics, or related discipline
  • Demonstrated experience in developing and training AI models
  • Strong knowledge of deep learning, NLP, and computer vision
  • Experience in scaling up generative models for production environments
  • Ability to collaborate in a team environment and explain technical concepts to non-technical stakeholders

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