AI Developer

The Senior AI Engineer will be responsible for developing optimizing and deploying cutting-edge AI and machine learning solutions. This role involves building scalable ML pipelines integrating AI models into production environments collaborating with cross-functional Agile teams and driving innovation through modern AI technologies.

• Develop and optimize machine learning models for business use cases such as:
  • Document automation
    
  • Customer segmentation
    
  • Risk assessment
    
• Design build and maintain scalable ML pipelines for production deployment.
  
• Ensure reliable scalable and high-performing AI model deployments with minimal downtime.
  
• Collaborate with Product Owners Data Scientists Software Engineers Designers Quality Engineers and ML Engineers within Agile squads.
  
• Build and maintain CI/CD pipelines for machine learning model lifecycle management including testing versioning and deployment.
  
• Monitor production models for:
  • Performance
    
  • Accuracy
    
  • Fairness
    
  • Model drift
    
  • Bias detection
    
• Create and maintain technical documentation for models pipelines and engineering processes.
  
• Participate in Site Reliability Engineering (SRE) activities to support production applications.
  
• Provide after-hours production support when required.
  
• Improve operational efficiency by implementing engineering best practices monitoring metrics and maintaining Service Level Agreements (SLAs).
  
• Stay current with emerging AI/ML technologies and share knowledge across engineering teams.
  

• Strong programming experience in:
  • Python
    
  • Java
    
  • C
    
• Experience with software development best practices and Agile methodologies.
  

• Experience working with cloud platforms:
  • AWS
    
  • Microsoft Azure
    
  • Google Cloud Platform (GCP)
    
• Experience with MLOps tools and production ML deployment.
  

• 2 years of hands-on experience developing and optimizing machine learning models.
  
• Strong understanding of advanced machine learning algorithms and techniques.
  
• Experience building and deploying production-grade ML solutions.
  

• Hands-on experience with:
  • LangChain
    
  • Hugging Face Transformers
    
  • OpenAI APIs
    
• Experience integrating LLMs into enterprise applications.
  
• Experience evaluating LLM performance using appropriate metrics.
  

• Strong understanding of NLP concepts including:
  • Named Entity Recognition (NER)
    
  • Text Summarization
    
  • Text Classification
    
  • Information Extraction
    

• Production monitoring and model lifecycle management.
  
• CI/CD automation for ML applications.
  
• Model governance fairness and bias monitoring.
  
• Site Reliability Engineering (SRE) practices.
  
• Cross-functional collaboration in Agile development environments.