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Lead ML Ops Engineer
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CliftonLarsonAllen
Milwaukee, WI (In Person)
Full-Time
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Job Description
Lead ML Ops Engineer CliftonLarsonAllen parental leave, flex time, 401(k) United States, Wisconsin, Milwaukee Jun 08, 2026 LA 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. 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.
Our Perks:
Flexible PTO (designed to offer flexible time away for you!) Up to 12 weeks paid parental leave Paid Volunteer Time Off Mental health coverage Quarterly Wellness stipend Fertility benefits Complete list of benefits here CLA is growing and seeking to hire an experienced Lead Machine Learning Operations Engineer to join our talented team. This role manages a team of Machine Learning Operations Engineers, oversees the endtoend machinelearning strategy and execution, sets vision for MLOps, and ensures alignment with business goals. How you'll create opportunities in this role:- Define and execute an enterprise AI/ML platform strategy, encompassing MLOps, LLMOps, and AIOps, and build reusable frameworks and standards adopted across multiple projects and business units.
- Oversee enterprisescale AI platforms supporting model training, inference, evaluation, monitoring, retraining, and governance, including generative AI systems.
- Align AI and MLOps initiatives with business objectives, ensuring platforms and pipelines meet scalability, performance, security, regulatory, and cost requirements, including responsible and ethical AI considerations.
- Implement and enforce best practices for model and prompt versioning, monitoring, retraining, and automated workflows, ensuring consistent and reliable AI operations.
- Lead teams delivering shared AI infrastructure, tooling, and platforms, providing daytoday leadership through coaching, development, and performance management.
- Ensure platform reliability and operational excellence by overseeing escalated issue resolution, maintaining highquality documentation, and driving continuous improvement.
- Track and evaluate industry trends in AI platforms, LLM ecosystems, and AI operations, translating insights into roadmap decisions and platform evolution.