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# AI and Data Science Engineer III

- **Company:** Deloitte T.T.L.
- **Location:** United States
- **Salary:** $102,500 - $170,900
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Information Systems, Information Engineering, Global Positioning Systems (GPS), Python (Programming Language), Machine Learning, Natural Language Processing, Cloud Services, Software Engineering, SQL Databases, Management of Software Versions, Google Cloud, Large Language Models, Model Validation, Generative AI, Information Technology, Data Lineage, Data Analytics, Machine Learning Operations, Databricks
- **Published:** October 21, 2026
- **Apply:** https://apply.deloitte.com/en_US/careers/Login?jobId=372166

## About the Role

* Ability to work independently and collaborate as part of a team
 * Effective written and verbal communication skills
 * Meticulous attention to detail and quality of work product
 * Ability to build and sustain professional relationships
 * Ability to lead projects or workstreams
 * Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
 * Strong interpersonal skills and professional demeanor
 * Ability to meet deadlines
 * Ability to provide clear guidance to others, Required:
 * Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or Information Systems
 * 3+ years of experience developing data pipelines, machine-learning models, or artificial intelligence applications using Python and Structured Query Language (SQL).
 * 1+ year of experience using Git and continuous integration/continuous delivery pipelines to deploy software, data, or machine-learning solutions.
 * Active Secret Security Clearance or higher
 * You must reside within a commutable distance of your assigned office with the ability to commute daily, if required, without the need for overnight accommodations.
 * You can expect to co-locate on average up to 5 times a week with variations based on types of work/projects and client locations.
 * Ability to travel up to 25%, on average, based on the work you do and the clients and industries/sectors you serve.
 * Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

 * Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or Information Systems.
 * 1+ year of experience deploying models through managed cloud services on Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
 * 2+ years of experience using Databricks or Palantir for data engineering or analytics workflows.
 * 1+ year of experience with natural language processing, large language models, or generative artificial intelligence.
 * 1+ year of experience implementing machine learning operations (MLOps) practices for model monitoring, versioning, and deployment.
 * 1+ year of experience delivering data, analytics, or artificial intelligence solutions for federal, state, local government, or public higher education clients.

## Description

Join Deloitte's AI & Engineering team to help clients modernize technology platforms, accelerate innovation, and drive meaningful business outcomes. In this role, you will work alongside multidisciplinary professionals to design and deliver modern data solutions that support enterprise transformation. You will help build scalable platforms, analytics products, and data pipelines that enable mission-focused results and measurable client impact., As an AI and Data Science Engineer III on the Government & Public Services (GPS) AI & Data team, you will be responsible for designing, developing, and deploying data and AI solutions that support client missions.

 * Design and build data pipelines, machine-learning models, and AI-enabled applications using Python, Structured Query Language (SQL), and cloud-based services.
 * Translate mission and business requirements into technical designs, data models, and implementation plans.
 * Develop, test, deploy, and monitor scalable analytics and artificial intelligence solutions using software engineering and machine learning operations practices.
 * Collaborate with product, engineering, analytics, and client stakeholders to integrate data and AI capabilities into platforms and business processes.
 * Document solution architecture, model performance, data lineage, and operational procedures to support delivery, governance, and sustainment.