AI/ML Engineer - Clearance Required

Overview

LMI is seeking an Artificial Intelligence and Machine Learning (AI/ML) Engineer to support a Special Operations Command (SOCOM) mission partner with production machine learning, predictive forecasting, natural language processing, generative AI, and real-time decision-support capabilities. The AI/ML Engineer will design, implement, optimize, integrate, and sustain scalable AI/ML solutions within secure web-based applications and enterprise workflows. This position will work as part of a cross-functional data science product team to translate validated models into reliable operational capabilities while advancing reusable engineering patterns, governance, security, documentation, and enterprise AI/ML best practices.

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 achieve mission success.

This position requires an active Secret security clearance with the ability to obtain a Top Secret clearance.
Responsibilities

- Design, implement, test, and optimize machine learning algorithms for predictive forecasting, rate prediction, resource planning, and real-time decision support.

- Develop and refine supervised, unsupervised, time-series, regression, ensemble, and other appropriate models to meet stringent accuracy, reliability, explainability, latency, and efficiency requirements.

- Develop natural language processing and generative AI solutions, including large language models and retrieval-augmented generation capabilities tailored to approved business, operational, and intelligence use cases.

- Engineer reusable model services, application programming interfaces, containers, and software components that integrate seamlessly into secure web-based applications, dashboards, and other mission data products.

- Design scalable and reliable architectures for batch and real-time inference, model serving, monitoring, and application support across development, test, and production environments.

- Integrate predictive models into existing web-based applications and enterprise workflows while ensuring compatibility, reliability, security, and seamless user functionality.

- Collaborate with data scientists and data engineers to establish compatible data structures, features, pipelines, interfaces, and validation methods for model training, evaluation, deployment, and sustainment.

- Conduct performance testing, hyperparameter tuning, error analysis, back-testing, drift detection, and model monitoring; document assumptions, limitations, risks, and opportunities for continued improvement.

- Implement MLOps and DevSecOps practices for source control, automated testing, continuous integration and delivery, model versioning, deployment, monitoring, rollback, and repeatable sustainment.

- Apply responsible and secure AI/ML engineering practices, including access control, data protection, model governance, explainability, evaluation, auditability, and risk management.

- Support enterprise synchronization, integration, governance, sustainment, and adoption of AI/ML capabilities across multiple mission teams, stakeholder organizations, applications, and products.

- Develop projects that automate or augment human cognitive workload and respond rapidly to emerging operational requirements and changes in the mission environment.

- Produce and maintain technical documentation covering algorithms, system architecture, interfaces, security, testing, deployment, operations, and