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 2026 (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)