Applied Machine Learning Engineer

Take models from notebooks to production systems that serve real operational workflows.

• Convert data science ideas into reliable model services.
• Build feedback loops that improve model performance over time.
• Help teams use AI where it creates measurable operational value.

• Implement training, inference, feature, evaluation, and monitoring pipelines.
• Work with data scientists to harden models for production use.
• Build APIs, batch jobs, and workflows around ML capabilities.
• Improve model reliability, latency, cost, and explainability.

• 4+ years of ML engineering or applied machine learning experience.
• Strong Python and production software fundamentals.
• Experience deploying models or ML-powered services.
• U.S. Citizenship is required.
• Must be capable of obtaining and maintaining a Top Secret security clearance.
• Comfort working with ambiguous mission, data, and engineering problems.
• Strong written communication and ability to explain technical decisions to technical and non-technical teams.

• AWS experience is a plus, especially secure cloud, Gov Cloud, serverless, data, or AI services.
• AI, machine learning, LLM, agentic workflow, or decision intelligence experience is a plus.
• Experience in defense, government, manufacturing, aerospace, logistics, or other mission-critical environments is a plus.