• Data Preprocessing:
  
• Collect, clean, and preprocess data for machine learning pipelines.
  
• Perform exploratory data analysis to uncover patterns and insights.
  
• Model Development:
  
  • Assist in building, training, and fine-tuning machine learning models.
    
  • Implement algorithms in supervised, unsupervised, and reinforcement learning.
    
• System Integration:
  
  • Integrate AI/ML models into existing or new software systems.
    
  • Test, validate, and deploy machine learning solutions.
    
• Research and Experimentation:
  
  • Stay updated on the latest AI/ML technologies and research.
    
  • Experiment with novel algorithms and techniques to improve performance.
    
• Performance Monitoring:
  
  • Evaluate model performance using metrics such as accuracy, precision, recall, etc.
    
  • Optimize models for speed and scalability.
    
• Collaboration:
  
  • Work closely with cross-functional teams, including data scientists, software engineers, and product managers.
    
  • Contribute to code reviews and provide constructive feedback.
    

Requirements