AI Engineer

Design, develop, and deploy LLM-based applications.

Build Retrieval-Augmented Generation (RAG) solutions to enhance LLM capabilities.

Conduct experiments to validate hypotheses and improve application performance and accuracy.

• Collect, clean, and pre-process both structured and unstructured data.
  

• Perform Exploratory Data Analysis (EDA) to uncover trends and actionable insights.
  

  • Monitor and ensure stability, scalability, and accuracy of deployed AI solutions.
    

  • Continuously refine applications based on user feedback and evolving requirements.
    

    • Work closely with data engineers, software developers, and business stakeholders to translate requirements into AI-driven solutions.
      

      • Maintain comprehensive documentation for workflows, technical designs, and processes.
        

      • Present findings and recommendations effectively to both technical and non-technical stakeholders.
        

        
        

        
        

        
        

        
        

        
        
        Requirements

        • Proficiency in Python, R, or JavaScript for AI/ML development and LLM applications.
          
        • Hands-on experience with ML/DL frameworks such as TensorFlow, PyTorch, or Scikit-learn.
          
        • Solid understandings of data structures, algorithms and statistical methods.
          
        • Strong knowledge in Natural Language Processing (NLP), Computer Vision (CV), or Reinforcement Learning (RL).
          
          
          
          Benefits

          • Opportunities for professional development, including upskilling and attending AI-focused conferences.
            

          • Comprehensive health insurance for you.
            

          • An Apple accessory for use.
            

          • Catered lunch in the office.
            

            
            
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