Mid-Level AI/ML Solutions Engineer

AgileATS, LLC.; Corridor North (MD); On-site; USD 188,000 - 223,000; Full time

Job summary

AgileATS, LLC. is seeking an AI/ML Engineer with a TS/SCI polygraph security clearance to design, build, test, and productionize advanced machine learning models that support mission-critical tasks.

You will architect data pipelines, select representations, run analyses, and iteratively refine models, guiding test protocols and ensuring scalable, reliable AI systems. In this role you lead the lifecycle from prototype to production, collaborating across teams to deliver accurate predictions at

Responsibilities

• Design, build, test, and productionize advanced AI/ML models
• Architect data pipelines and select optimal representations
• Run statistical analyses and refine models iteratively
• Lead testing protocols and assess data distribution shifts
• Ensure scalable, mission-critical AI systems

Job description

ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED

We are seeking a visionary, inventive Artificial Intelligence / Machine Learning (AI/ML) Engineer to design, build, test, and productize advanced models that solve high-stakes challenges. In this role, you won't just train models in isolation—you will transform data science prototypes into production-ready, scalable AI solutions. You will oversee the complete lifecycle: architecting data pipelines, selecting optimal representations, running statistical analyses, and continuously refining models through iterative feedback and retraining loops. As a technical leader and primary subject matter expert, you will guide test and evaluation protocols, evaluate data distribution shifts, and ensure our AI systems deliver accurate, mission-critical predictions at scale.

The annual base salary range for this role is $188,000-$223,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.