GEICO is looking to lead the technical architecture and delivery of AI solutions that span multiple functional and technical boundaries, define and own the vision for scalable, robust, and compliant AI/ML solutions, and drive high-visibility, cross-functional initiatives from ideation through production to accelerate transformation and deliver measurable value across the enterprise.
Requirements
- Strong proficiency in Python and SQL; deep experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn
- Demonstrated experience establishing KPI frameworks, experimentation, and causal analysis to quantify model impact and inform prioritization.
- Experience with GenAI and LLMs (e.g., prompt design, RAG, evaluation strategies, guardrails, red-teaming, human-in-the-loop workflows).
- Record of patents, peer-reviewed publications, or meaningful open-source contributions.
- Familiarity with insurance operations and model governance in regulated environments.
Responsibilities
- Provide architectural leadership for AI/ML solutions impacting multiple stakeholders. Establish standards for scalability, reliability, observability, compliance, and cost efficiency across online and batch systems.
- Lead end-to-end delivery of AI/ML solutions, including model design, data pipelines, feature stores, evaluation, deployment, A/B testing, and monitoring in real-time and batch environments. Ensure clear plans, milestones, and on-time delivery.
- Establish robust mechanisms to quantify business impact, including KPI definition, experimentation frameworks, and causal inference approaches to guide decision-making and prioritize investments.
- Stay current with cutting-edge research in ML, GenAI, and optimization. Prototype and harden novel techniques that push the boundaries of innovation within GEICO’s insurance ecosystem.
- Elevate technical standards (coding, testing, documentation, reproducibility), and foster a culture of scientific rigor and engineering excellence.
- Translate complex technical topics into clear narratives for technical and non-technical audiences.
- Present to senior stakeholders, set context, explain trade-offs, and build alignment and enthusiasm.
Other
- Master’s or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience with an exceptional track record.
- At least 6+ years of professional experience delivering applied AI/ML solutions in production, including leading cross-functional initiatives with enterprise impact.
- Excellent stakeholder management skills with a track record of driving alignment and adoption across product, engineering, and business teams.
- Strong written and verbal communication skills; ability to set the right context and explain complex technical topics to varied audiences, including executives.
- Candidates must be open to the following locations: Chevy Chase, Maryland, Palo Alto, CA, New York City, NY
