Azure AI Architect

• Envision build deploy and operationalize an endtoend machine learning (ML) and AI pipeline
  
• Build a robust enterprise wide architecture for AI and collaborate with data scientists data engineers developers operations and security
  

• Requirement analysis: Analyzing what an organization needs and how AI can help
  
• Solution design: Designing AI solutions that are scalable costeffective and in alignment with the organization s goals
  
• Technology selection: Selecting the appropriate technology stack and tools that will be used to build the AI system
  
• Auditing: Conducting a comprehensive audit of AI tools and practices including data models and software engineering emphasizing continuous improvement. Establishing a feedback loop to evaluate AI services facilitate model recalibration and retrain models as needed
  
• Implementation: Overseeing the implementation of the AI system and ensuring it meets the organization s requirements
  
• Monitoring and maintenance: Monitoring the performance of the AI system troubleshooting issues and ensuring the system is maintained and updated regularly
  
• Has a holistic understanding of the business landscape combined with a grasp of AI capabilities allowing them to guide AI projects towards success
  
• To work in team collaboration with crossfunctional teams including technical architects data engineers and domain experts to understand business requirements and develop effective AI solutions
  
• To be diligent in learning / scaling up in the areas of Data ScienceAI with selfinitiative towards career excellence
  

Requirements

• Bachelors degree in Computer Science Software Engineering or related fields
  
• 5 years of practical experience in designing and developing AI platforms (Azure is preferred)
  
• Ability to communicate at a business level in both English and Japanese and to collaborate with internal and external stakeholders
  

• Deep understanding and practical experience in AIrelated technologies such as machine learning deep learning natural language processing and computer vision
  
• AI architecture and pipeline planning. Understand the workflow and pipeline architecture of ML and deep learning workloads. An indepth knowledge of components and architectural tradeoffs involved across the data management governance model building deployment and production workflows of AI is a must
  
• Software engineering and DevOps principles including knowledge of DevOps workflows and tools such as Git containers Kubernetes and CI/CD
  
• Data science and advanced analytics including knowledge of advanced analytics tools (such as SAS R and Python) along with applied mathematics ML and Deep Learning frameworks (such as TensorFlow) ML techniques (such as random forest and neural networks) and developing largescale models using AI frameworks such as TensorFlow PyTorch and Keras
  
• Experience in designing and developing AI systems using cloud platforms (Google AWS Azure etc.)
  
• Knowledge of AI model operations and deployment (model optimization monitoring version control etc.)
  
• Practical experience in largescale data processing technologies (BigQuery Spark Hadoop etc.)
  
• Knowledge of AI ethics and privacy and ability to incorporate them into AI system design
  

• Native level Japanese ideally Business level English in reading writing and speaking
  

• Envision, build, deploy and operationalize an end-to-end machine learning (ML) and AI pipeline
  
• Build a robust enterprise wide architecture for AI and collaborate with data scientists, data engineers, developers, operations and security
  

• Requirement analysis: Analyzing what an organization needs and how AI can help
  
• Solution design: Designing AI solutions that are scalable, cost-effective, and in alignment with the organization s goals
  
• Technology selection: Selecting the appropriate technology stack and tools that will be used to build the AI system
  
• Auditing: Conducting a comprehensive audit of AI tools and practices, including data, models, and software engineering, emphasizing continuous improvement. Establishing a feedback loop to evaluate AI services, facilitate model recalibration, and retrain models as needed
  
• Implementation: Overseeing the implementation of the AI system and ensuring it meets the organization s requirements
  
• Monitoring and maintenance: Monitoring the performance of the AI system, troubleshooting issues, and ensuring the system is maintained and updated regularly
  
• Has a holistic understanding of the business landscape, combined with a grasp of AI capabilities, allowing them to guide AI projects towards success
  
• To work in team collaboration with cross-functional teams, including technical architects, data engineers, and domain experts, to understand business requirements and develop effective AI solutions
  
• To be diligent in learning / scaling up in the areas of Data Science-AI with self-initiative towards career excellence
  

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or related fields
  
• 5+ years of practical experience in designing and developing AI platforms (Azure is preferred)
  
• Ability to communicate at a business level in both English and Japanese, and to collaborate with internal and external stakeholders
  

• Deep understanding and practical experience in AI-related technologies such as machine learning, deep learning, natural language processing, and computer vision
  
• AI architecture and pipeline planning. Understand the workflow and pipeline architecture of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI is a must
  
• Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD
  
• Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow), ML techniques (such as random forest and neural networks) and developing large-scale models using AI frameworks such as TensorFlow, PyTorch, and Keras
  
• Experience in designing and developing AI systems using cloud platforms (Google, AWS, Azure, etc.)
  
• Knowledge of AI model operations and deployment (model optimization, monitoring, version control, etc.)
  
• Practical experience in large-scale data processing technologies (BigQuery, Spark, Hadoop, etc.)
  
• Knowledge of AI ethics and privacy, and ability to incorporate them into AI system design
  

• Native level Japanese, ideally Business level English in reading, writing and speaking