Lead the advancement of Business Insurance's MLOps and LLMOps practices across the full modeling lifecycle, driving end-to-end automation, observability, and scalability of our predictive models.
Own and execute a technical roadmap focused on deployment automation, feature management, model monitoring & observability, and tools for GenAI and agentic solutions.
Partner closely with data scientists, architects, and technology teams to help shape Business Insurance's MLOps strategy.
Streamline processes and standardize implementation patterns to accelerate the delivery of high-quality, reliable ML and AI solutions at scale.
Execute data strategies to support various consumption patterns and identify enterprise architecture, platform, and application infrastructure needs.
Drive the operationalizing and automating of all capabilities to ensure secure, supported and scalable solutions.
Present analysis and recommendations to help influence management and executive leadership decisions.
Guide and coach senior team members to accelerate career development.
Establish budgets, policies and practices with significant impact on area operations.

Requirements

Bachelor’s Degree in STEM related field or equivalent.
Eight or more years of related work experience.
Four or more years of team leadership experience.
Proven experience advancing MLOps implementation and deployment practices from foundational to mature operational states.
Demonstrated ability to lead cross-functional execution while contributing to strategic planning and organizational direction.
Experience managing technical teams of 3-4 direct reports, with capability to oversee Director-level personnel as the organization scales.
Strong background in artificial intelligence and machine learning with depth exceeding traditional data engineering experience.
Hands-on experience with industry-standard ML frameworks and platforms, including: Cloud ML Services (AWS SageMaker), Data Science Platforms (Databricks), Machine Learning Algorithms (Gradient Boosting Models), Deep Learning Frameworks (PyTorch, TensorFlow), and DevOps Practices (CI/CD, Automated Deployment, Automated Testing).
Interest and aptitude for emerging technologies including Large Language Models (LLM's), Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG) Systems.
Subject matter expertise in data tools, techniques, and manipulation including cloud platforms, programming languages, and technology platforms.

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

MLOpsLLMOpsdeployment automationmodel monitoringfeature managementmachine learningartificial intelligencecloud ML servicesdeep learningdata manipulation

Soft Skills

leadershipstrategic planningcross-functional executioncoachingcommunicationinfluencingbudget managementpolicy establishmentprocess streamliningteam development

Certifications

Bachelor’s Degree in STEM