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GenAI Engineer

  • Full Time, onsite
  • Orion Business Innovations Careers
  • Hybrid2 days/week in office, United States of America
Salary undisclosed

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Generative AI Engineer

Responsibilities:

  • Integration and Collaboration: Collaborate with cross-functional teams to integrate generative AI solutions into existing workflow systems. Document and present complex findings and learnings in a clear and concise manner to a non-technical audience.
  • Research and Innovation: Stay up-to-date on the latest advancements in generative AI technologies and methodologies such as Retrieval Augmented Generation (RAG), Vector Databases, frameworks such as langchain, etc.
  • Algorithm Development: Design and develop algorithms for generative models using deep learning techniques, Natural Language Processing (NLP), Retrieval Augmented Generation (RAG) etc.
  • Model Architecture Design: Create and fine-tune generative neural network architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer-based models.
  • Data Management: Clean, label, and augment data for training and improving AI models.
  • AI Alignment and Testing: Perform rigorous testing and validation of generative AI models to ensure their robustness and reliability. Address ethical considerations related to generative AI, such as bias, fairness, and transparency.

Qualifications:

Education: Bachelor s or Master s degree in Computer Science, Data Science, or a related field.

Experience: At least 5 years of experience in backend development and machine learning.

Technical Skills:

  • Strong proficiency in Python and AI frameworks (TensorFlow, PyTorch).
  • Proven experience in developing and implementing generative AI models, with a strong understanding of machine learning algorithms.
  • Solid understanding data pre-processing techniques.
  • Knowledge of cloud computing and AI deployment (Azure, AWS, Google Cloud) is a plus.
Education: Bachelor s or Master s degree in Computer Science, Data Science, or a related field.
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