Staff Machine Learning Engineer

GEICO•Palo Alto, CA

About The Position

We are seeking an accomplished Senior Staff ML Engineer who will serve as a technical leader for Generative AI applications at GEICO. In this individual contributor role, you will be collaborating with a dynamic team of AI and software engineers to design, develop, and deploy systems that ensure scalability, reliability and usability of generative AI solutions, applications, and workflows across the organization which drive business value using LLM, agentic, and knowledge-search capabilities as their foundation. You bring a passion for providing hands-on guidance, ensuring architectural and technical excellence and best practices, serving as a source of thought leadership, and leading by example to solve complex, large-scale, cross-functional problems.

Requirements

8+ years of experience designing and building scalable production AI/ML applications and systems in cloud environments
5+ years owning end-to-end development, monitoring, maintenance, and continuous improvement of scalable, robust AI/ML applications.
5+ years of experience with training, finetuning, real-time/batch inferencing, and evaluation systems for AI/ML models and LLMs used in production systems
5+ years of experience managing the end-to-end software development life cycle (e.g. CI/CD pipelines, Kubernetes-based deployments, testing, monitoring & alerting, production support etc.) for Generative AI applications, backend systems, and APIs
Experience using frameworks to build LLM-based agentic workflows such LangSmith/LangGraph or similar
Experience using typical agentic communication standards such as A2A, MCP, and similar to design, architect, and build working multi-agent applications
Proficient in Python, Java or similar general-purpose programming languages.
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Nice To Haves

5+ years interfacing directly with internal business stakeholders and/or external stakeholders on AI/ML initiatives
Extensive experience using cloud provider solutions such as Azure and AWS to deploy and maintain AI/ML products
Extensive experience using tools that power production-grade LLM-based AI agents, such as eval frameworks, agent tooling, RAG pipelines, prompt engineering, etc.
Experience building products with LLM-based AI agent workflows via both no code/low code and traditional high-code development environments
Experience with agentic workflows to solve problems in the insurance domain
Strong communication and problem-solving skills to excel in dynamic, cross-functional and ambiguous decision-making environments

Responsibilities

Own end-to-end design, development, and maintenance of high-performance AI solutions that use agentic workflows to deliver concrete business value for internal stakeholders and customer-facing applications. Examples include AI agent orchestration, conversational AI solutions, knowledge assistants, process assistance and automation, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, and designers to gather requirements, define project scope and prioritize feature development.
Establish pragmatic technical visions and roadmaps that balance business outcomes, product release timelines, and engineering excellence.
Integrate and build solutions using GEICO’s AI platform architecture.
Partner with platform teams to communicate requirements, understand current capabilities and gaps, and contribute to platform feature roadmaps and development.
Ideate, define, and build first-of-its-kind solutions within GEICO, with a deep understanding of business and technical processes, applications, and architecture to guide development.
Drive the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Take ownership in project planning and stakeholder management, driving technical alignment, ensuring efficient resource allocation, and timely delivery of solutions.
Mentor and guide junior engineers via code reviews and design sessions, establish and enforce best practices, and foster a collaborative and high-performance team culture.