Lead ML Ops Engineer

About the role

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.

Responsibilities

• 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.

Requirements

• 6 years of relevant experience required.
• Experience in MLOps, DevOps, or related fields, with a focus on enterprise-level solutions preferred.
• Supervisory experience preferred.

Qualifications

• Bachelor's degree is required.
• 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/TypeScript, and enterprise platforms (e.g., .NET).
• Leadership-level expertise in AI/ML platform engineering, spanning MLOps, LLMOps, and AIOps.
• 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.

Skills

• Advanced proficiency in Python
• Architectural mastery of object-oriented design across dynamically typed languages
• Broad experience integrating and governing multi-language systems
• Leadership-level expertise in AI/ML platform engineering
• Deep understanding of AI system observability
• Strong experience with cloud architecture, security, compliance, and enterprise-scale deployments
• Proven ability to guide teams in technical decision-making and platform strategy

Benefits

Wellness at CLA 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. To view a complete list of benefits, click here.

Pay

TBD

Schedule

TBD