Senior Machine Learning Operations Engineer - CliftonLarsonAllen

CLA is a top 10 national professional services firm w ur purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.

CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.

CLA is growing and seeking to hire an experienced Senior Machine Learning Operations Engineer to join our talented Information Technology team. The position offers growth, flexibility and a collaborative work environment.

In this position you should have the following; excellent interpersonal skills with the ability to communicate at all levels. Strong problem solving and creative skills and the ability to exercise sound judgment. Most important, demonstrate a high level of integrity and dependability with a strong sense of urgency and results-orientation.

This role leads the design, development, and deployment of advanced machine learning models and the supporting MLOps infrastructure.

How you’ll create opportunities in this Senior Machine Learning Operations Engineer role:

• Lead the design and implementation of AI/ML platform and MLOps infrastructure, enabling deployment, management, monitoring, and governance of ML models, LLMs, NLMs, and SLMs in production environments.
• Collaborate cross-functionally to integrate AI and machine learning capabilities into production systems, translating business requirements into scalable technical solutions.
• Implement and enforce best practices across MLOps and LLMOps, including model and prompt versioning, feature management, monitoring, evaluation, retraining, and governance.
• Design and operate reliable inference and orchestration patterns for AI systems, supporting batch, real-time, and event-driven workloads.
• Troubleshoot and resolve complex issues across models, AI services, data pipelines, and infrastructure, ensuring reliability, security, scalability, and performance at scale.
• Create and maintain technical and operational documentation, support escalations, and mentor junior engineers to raise team capability and consistency.
• Evaluate emerging AI platform technologies, tools, and frameworks, guiding adoption aligned with business needs and platform strategy.

What you will need:

• Experience in MLOps, DevOps, or related fields
• Bachelor's degree or a combination of relevant experience and training may be considered in lieu of a degree.

Technical Competencies: