Lead ML Ops engineer

## Lead ML Ops engineer

Apply locations:
Arlington, VA:
Nashville, TN:
Racine, WI:
Connection Center-Tempe,AZ:
Austin, TXtime type:
Full time posted on:
Posted Todayjob requisition :
R17467LA 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 end‐to‐end machine‐learning 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 enterprise‐scale 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 day‐to‐day leadership through coaching, development, and performance management.
• Ensure platform reliability and operational excellence by overseeing escalated issue resolution, maintaining high‐quality 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.
*
* What you will need:

** 6 years of relevant experience required.
* Experience in MLOps, Dev Ops, or related fields, with a focus on enterprise-level solutions preferred.
* Supervisory experience preferred.
** Education
* * Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.
* Degree in computer science, data science, or related field preferred.
** Technical Competencies
*** Advanced proficiency in Python and architectural mastery of object‐oriented design across dynamically typed languages.
* Broad experience integrating and governing multi‐language systems, including Python, JavaScript/Type Script, and enterprise platforms (e.g., .NET).
* Leadership‐level expertise in AI/ML platform engineering, spanning MLOps, LLMOps, and AIOps.
* Ability to define and enforce enterprise standards for AI model lifecycle management, monitoring, reliability, and cost control.
* Deep understanding of AI system observability, including drift detection, evaluation frameworks, and incident response.
* Strong experience with cloud architecture, security, compliance, and enterprise‐scale deployments.
* Proven ability to guide teams in technical decision‐making and platform strategy.
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