Lead AI Engineer (Machine Learning)

Renuity • Charlotte, NC

1d

About The Position

The Lead AI Engineer (Machine Learning) will design, build, and deploy production-ready ML and deep learning solutions that deliver measurable business impact. In this role, you will partner closely with product, engineering, and business stakeholders to translate complex problems into scalable, data-driven systems that are embedded into everyday workflows. This role combines strong software engineering with ML best practices; taking problems from discovery through production launch and ongoing improvement.

Requirements

• Master’s degree in a related field (e.g., Computer Science, Data Science, Statistics, Applied Mathematics, Engineering) or equivalent practical experience with demonstrated production delivery.
• 6+ years of experience in applied machine learning, with clear examples of models shipped to production.
• Expertise in both Python and SQL coding (other coding languages such as Java, C#, etc. are a plus)
• Experience with at least one major cloud platform (Azure is preferred; GCP, AWS are also acceptable) and production logging/monitoring practices.
• Strong software engineering skills (building services/APIs, code reviews, testing, CI/CD familiarity).
• Demonstrated ability to translate ambiguous business problems into practical, measurable solutions.
• Comfortable working cross-functionally with Product, Engineering, Operations, and business leaders.

Responsibilities

• Deliver end-to-end ML/DL solutions that drive measurable outcomes (conversion lift, cost reduction, improved forecasting accuracy, etc.).
• Partner with business and product stakeholders to define success metrics, scope solutions, and ensure adoption in day-to-day workflows.
• Build, test, and deploy ML services and applications that integrate with core systems (e.g., CRM, call center tooling, scheduling, reporting).
• Implement reliable production practices: monitoring, alerts, model performance tracking, and continuous retraining/iteration when needed.
• Improve data readiness by partnering with analytics/data engineering to define data requirements, quality checks, and reusable datasets.
• Contribute to team standards for documentation, code quality, and responsible AI practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees