Director, Machine Learning Engineering
Overview
The Director – Runtime Intelligence & Personalization role at GEICO is responsible for leading the development of intelligent runtime systems that power context-aware, personalized experiences across products and platforms. This role sits at the intersection of AI/ML, platform engineering, and product strategy, focusing on building scalable systems that leverage context, memory, and retrieval to deliver differentiated, real-time intelligence.
Key Responsibilities
Define and execute the roadmap for runtime intelligence capabilities, including context building, memory systems, and RAG-based architectures.
Translate business and customer needs into scalable, AI-powered personalization strategies.
Partner with executive stakeholders to align runtime intelligence investments with enterprise priorities.
Lead development of core runtime capabilities: Context orchestration and state management, Memory systems (short-term and long-term), Retrieval systems (RAG, knowledge integration), Personalization frameworks.
Drive design and implementation of high-scale, low-latency systems ensuring systems are secure, observable, and reliable in production environments.
Establish observability standards across runtime intelligence systems (latency, quality, accuracy, cost).
Define KPIs and metrics to evaluate system performance and business impact.
Lead continuous optimization of runtime performance, cost, and response quality.
Implement feedback loops for model and system improvement.
Oversee end-to-end delivery of runtime intelligence platforms, ensuring scalability and reliability.
Manage prioritization, trade-offs, and execution in a complex, fast-paced environment.
Build, lead, and scale high-performing teams across engineering, ML, and platform functions.
Develop talent strategy, including hiring, coaching, and organizational design.
Foster a culture of innovation, accountability, and continuous improvement.
Lead through senior managers and technical leaders to deliver outcomes at scale.
Partner with Product, Design, Data, and Infrastructure teams to deliver integrated solutions.
Influence senior stakeholders and drive alignment across competing priorities.
Communicate complex technical concepts clearly to executive and non-technical audiences.
Qualifications
10–15+ years of experience in engineering, platform, or AI/ML roles, with significant leadership experience.
Proven track record building and scaling distributed systems, AI platforms, or personalization systems.
Deep expertise in areas such as: Retrieval-Augmented Generation (RAG), Context and memory architectures, Real-time inference systems.
Strong business acumen with the ability to translate strategy into execution.
Demonstrated success leading large, complex, cross-functional initiatives.
Preferred Experience
With LLMs, generative AI, and agent-based systems.
Background in observability, experimentation frameworks, or system optimization.
Experience operating in high-scale, customer-facing environments.
Core Competencies
Strategic Thinking & Vision.
AI/ML & Platform Leadership.
Operational Excellence & Execution.
Cross-Functional Influence.
Talent Development & Leadership.
Data-Driven Decision Making.
Pay
$150,000.00 - $300,000.00