Lead ML Ops engineer

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.

• 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

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 machine learning strategy and execution, sets vision for MLOps, and ensures alignment with business goals.

• 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 daytoday 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.

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.

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.

• 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.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

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.