AI Engineer Intern (USPS) - Summer 2026

Overview

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors-helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

*This position is currently full-time onsite at the customers Washington DC office.

Responsibilities

• Identify opportunities where AI/ML or modeling and simulation can generate business insights or improve business processes

• Develop and implement digital and analytic approaches

• Work with product designers, application developers, infrastructure engineers, and other data scientists to integrate predictive and prescriptive models with web-based applications

• Research algorithms in machine learning to identify viable approaches to meet business requirements

• Apply machine learning methods, such as natural language processing (NLP), computer vision, regression, clustering, classification, and deep learning

• Design solution prototypes that connect to data sources and deploy through services, such as service functions in web applications or application programming interfaces (APIs)

• Become familiar with DevSecOps principles to continuously deliver high-quality software

• Work with Docker to develop and deploy containerized versions of models

• Participate in design and code reviews, and collaborate with a strong, passionate engineering team

• Provide input to UX/UI designers and front-end application developers on how to effectively deliver model outcomes to users

• Interface with customer stakeholders to provide technical explanations and support

Qualifications

• Pursuit of a Bachelor's degree (Graduate student highly preferred) in engineering, mathematics, computer science, or related technical discipline required .

• Currently enrolled in a Graduate (Masters) program highly preferred

• Pursuing a post-graduate or undergrad degree in engineering, mathematics, computer science, modeling and simulation, operations research, or related technical discipline

• Must be able to work for a minimum of 10-12 weeks beginning in Summer 202 6 (May/June)

• Comfortable working with agile teams, developing prototypes and functionality in short development sprints

• Ability to work independently and collaborate effectively with a project team in an agile research and development environment

• Comfortable using Atlassian products, including JIRA, Bamboo, Confluence, FishEye , Crucible, and Bitbucket

• Ability to think critically to propose tractable solutions to complex problems

• Effective written and verbal communication skills

• Ability to communicate complex concepts to both technical and business-focused audiences

• Familiarity or desire to excel with modern programming languages appropriate for machine learning prototyping; Python is preferred, but experience with other languages such as Java, C++, C#, JavaScript and R demonstrate the necessary ability

• Familiarity with the underlying mathematics of machine learning

• Knowledge of data structures and data management principles, methods, and tools

• Desire to explore machine learning frameworks and libraries, such as scikit-learn, TensorFlow, and Spark ML

• Ability to work with integrated development environments, such as Jupyter , JupyterLab , JetBrains IntelliJ IDEA, JetBrains PyCharm, JetBrains CLion, and Visual Studio Code

• Ability to collaborate with a team that develops applications using web development frameworks, such as Angular (1.x/2+), React, and Ember, and server frameworks, such as Node.js and Express.js
• Ability to consume or interface with cloud computing and storage services, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud
• Familiarity or desire to become familiar with containerization technologies, such as Docker, Kubernetes, Amazon Elastic Container Service (ECS), and Amazon Elastic Kubernetes Service (EKS)