Team structure: Typical AI Project Development

For developing the multi-phased AI solution, the following is a typical structure of the project team members, deployed as needed in respective phases:    

 

Consultant Roles* 

Consultant Name  

Location 

Delivery Manager & Project Manager 

Will be responsible for overall project planning, coordination, and management and will ensure that project objectives are met, timelines are adhered to, and resources are allocated effectively. 

TBD 

Seattle, WA, USA 

Lead Data Scientist 

Will be recommending appropriate analytics approaches and AI/ML algorithms for solutions in each phase and guide the team in designing the technical architecture and framework for solutions, based on project requirements. 

TBD 

Cupertino, CA, USA 

Technical Lead AI Engineer 

Will be designing and implementing the AI/ML solutions, leading the development of AI models, and ensuring successful integration and deployment of the AI solutions. 

TBD 

India 

Sr. Data Scientist 

Will identify relevant data sources, perform data preprocessing, develop AI/ML models, and ensure the accuracy and quality of the models. 

TBD 

India 

Data Scientist – Shadow 

Will perform data pre-processing and develop AI/ML models 

TBD 

India 

DevOps Engineer 

Will set up and maintain  the development and testing environments, as well as manage continuous integration and deployment processes. to ensure smooth operations and efficient deployment of the AI/ML solution. 

TBD  

India 

Data Engineer 

Will be responsible for data ingestion, data transformation, data quality assurance, and ensure the availability and reliability of data for analysis and model training throughout the project lifecycle.    

TBD 

India 

Quality Assurance Engineers (QA) 

Will be responsible for testing the solution, identifying, and reporting any issues or bugs, and ensuring that the solution meets the specified requirements and quality standards. 

TBD 

     Seattle (WA)  

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