AI/ML Engineer - Clearance Required

LMI Consulting, LLC; United States; On-site; USD 110,986 - 195,154; Full time

Job summary

LMI Consulting, LLC is seeking an AI/ML Engineer to support the U.S. Army's Holistic Health & Fitness initiative. This role involves developing and operationalizing analytic models for readiness assessment and injury-risk analysis.

The ideal candidate must have a Bachelor's degree in a relevant field and experience in statistical analysis and machine learning techniques. The position is remote with limited travel to Virginia for stakeholder engagement.

Qualifications

• Bachelor's degree in a relevant field.
• Demonstrated experience in statistical analysis and machine learning.
• Ability to maintain a Secret security clearance.

Responsibilities

• Develop and implement statistical and machine learning models.
• Collaborate with teams to align outputs with scientific intent.
• Support development of analytic workflows and documentation.

Skills

Statistical analysis

Machine learning techniques

Collaboration

Analytical reasoning

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Applied Mathematics

Job description

AI/ML Engineer - Clearance Required

Job Locations: US-Remote

Overview

LMI seeks an experienced AI/ML Engineer (Data Scientist) to support the U.S. Army's Holistic Health & Fitness (H2F) initiative as a member of the Analytics functional team within the H2F Program Support Team.

The AI/ML Engineer (Data Scientist) is responsible for developing, validating, and operationalizing analytic models, statistical methods, and machine learning approaches that support readiness assessment, injury‑risk analysis, and user engagement insights within the Holistic Health and Fitness Management System (H2FMS). This role focuses on applied analytics and model implementation, not independent analytic strategy or policy‑setting.

The AI/ML Engineer works closely with the Technical Project Manager, data engineers, data governance specialists, epidemiologists, research psychologists, tactical sports scientists, and software teams to translate Government‑directed analytic requirements into reproducible, interpretable, and scalable analytic solutions.

Responsibilities

• Develop and implement statistical and machine learning models supporting readiness assessment, performance analysis, and injury‑risk awareness.
• Apply appropriate analytic methods based on data characteristics, scientific guidance, and Government priorities.
• Ensure analytic approaches are transparent, interpretable, and suitable for operational decision support.
• Support validation, testing, and refinement of analytic models under Government and senior scientific direction.
• Assess model performance, limitations, assumptions, and potential bias.
• Collaborate with epidemiologists and research psychologists to ensure analytic outputs align with scientific intent.
• Work with data engineers to support feature development, data preparation, and analytic dataset construction.
• Assist in identifying data quality issues that may impact model performance.
• Ensure analytic inputs align with approved data definitions and governance standards.
• Collaborate with software teams to support integration of analytic outputs into dashboards, reports, and user‑facing decision‑support tools.
• Support development of repeatable analytic workflows and documentation.
• Assist in troubleshooting analytic issues in coordination with data and software teams.
• Contribute to documentation of analytic methods, assumptions, limitations, and results.
• Support preparation of analytic summaries, briefings, and materials for Government stakeholders.
• Clearly communicate analytic findings in a manner appropriate for non‑technical audiences.

Qualifications

Required Qualifications

• Bachelor's degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related field.
• Demonstrated experience applying statistical analysis or machine learning techniques to real‑world data problems.
• Familiarity with data preparation, feature engineering, and model evaluation concepts.
• Experience working with structured and semi‑structured data.
• Ability to collaborate effectively within multidisciplinary teams spanning analytics, research, and software development.
• Strong analytical reasoning and communication skills.
• Ability to obtain and maintain a Secret security clearance.

Desired Qualifications

• Experience supporting applied analytics in health, human performance, readiness, or research‑driven environments.
• Familiarity with integrating analytic outputs into dashboards or operational systems.
• Experience working alongside data engineering or software development teams.
• Prior experience supporting DoW or federal customers.

Location & Travel

• Duty Location: This position may be performed remotely.
• Travel: Limited travel to Fort Eustis, Virginia or LMI Headquarters may be required to support planning, integration, or stakeholder engagement.

Target salary range: $110,986 – $195,154

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only U.S. Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.

Equal Employment Opportunity

LMI is an Equal Opportunity Employer. LMI is committed to the fair treatment of all and to our policy of providing applicants and employees with equal employment opportunities. LMI recruits, hires, trains, and promotes people without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, disability, age, protected veteran status, citizenship status, genetic information, or any other characteristic protected by applicable federal, state, or local law. If you are a person with a disability needing assistance with the application process, please contact [e-mail].

Colorado Residents: In any materials you submit, you may redact or remove age‑identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.