Senior Machine Learning Operations Engineer

About the firm

CLA is a top 10 national professional services firm where our 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. 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.

About the role

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 role, you should have 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 importantly, 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.

Responsibilities

• 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.

Requirements

• 4 years of relevant experience required.
• 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.

Skills

• Advanced proficiency in Python and strong command of object-oriented design in dynamically typed languages.
• Proven experience designing and maintaining systems using multiple programming languages (e.g., Python, JavaScript/TypeScript, .NET) within complex platforms.
• Deep hands-on experience with AI/ML platform operations, supporting ML models, LLMs, NLMs, and SLMs in production.
• Strong expertise in MLOps and LLMOps, including model and prompt versioning, evaluation, monitoring, retraining, and governance.
• Ability to design and optimize scalable inference architectures (batch, real-time, and event-driven).
• Strong understanding of software engineering best practices, testing strategies, CI/CD, and system reliability.
• Advanced experience with cloud platforms, distributed systems, and performance optimization.

Benefits

To support our CLA family members, we focus on their physical, financial, social, and emotional well-being and offer comprehensive benefit options that include health, dental, vision, 401k, and much more.

View a complete list of benefits.

Pay

The compensation range for this position in Washington is $118,000.00 – $199,000.00. Our approach to compensation emphasizes collaboration and career growth. We pay competitive wages and view compensation as an investment in our people. Factors such as geography, experience, education, skills, and knowledge may impact the position of pay within the range.