AI/Digitalization Engineer

at  Deloitte

In this age of disruption, organizations need to navigate the future with confidence by tapping into the power of data analytics, robotics, and cognitive technologies such as Artificial Intelligence (AI). Our Strategy & Analytics portfolio helps clients leverage rigorous analytical capabilities and a pragmatic mindset to solve the most complex of problems. By joining our team, you will play a key role in helping our clients uncover hidden relationships from vast troves of data and transforming the Government and Public Services marketplace.

QUALIFICATIONS

Required:

• Bachelors degree
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
• Must have an Active Public Trust or above government security clearance
• 4+ years of experience developing Document AI processors to meet business needs
• 4+ years of experience training and testing models for accurate data extraction and parsing
• 4+ years of experience implementing API integrations
• 4+ years of experience in Machine Learning concepts, specifically document processing and NLP

Preferred:

• In depth understanding of SLDC
• Understanding of technology risks and the ability to assess and mitigate them
• Deep knowledge of a specific domain or industry, with a focus on computer science or software engineer
• Ability to display both breadth and depth of knowledge regarding functional and technical issues
• Experience presenting to clients or other decision makers to present and sell ideas to various audiences (technical and non-technical)

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.htm

The AI/Digitalization Engineer will be responsible for developing, training, testing, and refining AI models using Google Cloud’s Document AI. This involves integrating machine learning capabilities, managing large-scale document processing, and ensuring the model’s accuracy and efficiency through rigorous attention to detail and iterative refinement.