Senior Machine Learning Engineer

Location: New York

Senior Machine Learning Engineer Skip to main content

GEICO uses cookies to help us provide the best experience on GEICO Careers.  By continuing to use our website, you consent to the use of cookies.  For more information, please visit our cookie policy.#Senior Machine Learning Engineer page is loaded## Senior Machine Learning Engineer Apply remote type:
Hybrid locations:
New York City, NY:
Palo Alto, CA:
Bethesda, MDtime type:
Full time posted on:
Posted Todaytime left to apply:
End Date:
June 8, 2026 (4 days left to apply) job requisition :
R0064319
** At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
**** Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.
**** When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge:
Great Company, Great Culture, Great Rewards and Great Careers.
**** Senior Machine Learning Engineer, AI Research
**** About the Role
** GEICO is redefining the insurance landscape through cutting-edge Artificial Intelligence, and the AI Research team is driving this transformation. We are developing innovative, centralized, real-time AI solutions to solve complex business challenges and deliver advanced capabilities across claims, customer interactions, and operational efficiency.

As a Senior Machine Learning Engineer, you will play a pivotal role as a technical leader, designing, deploying, and managing production-grade ML systems that directly impact core business functions. This position is ideal for engineers who have experience shipping ML systems and seek greater ownership, technical depth, and significant business influence.

This is a hands-on opportunity for those passionate about scalable architectures, model robustness, and delivering operational excellence in advanced AI systems.
** What
* * You’ll Do
** Own End-to-End Production ML Systems
*** Design, implement, and deploy machine learning models and features for diverse AI applications including predictive analytics, automation, and decision support.
* Manage the complete ML lifecycle: data ingestion, feature engineering, training, evaluation, deployment, monitoring, and retraining.
* Continuously advance model performance, reliability, and interpretability in production environments.
** Build Scalable AI ML Pipelines
*** Develop scalable batch and real-time pipelines to support high-throughput AI workflows and applications.
* Optimize ML serving systems for speed, reliability, and cost-effectiveness.
* Collaborate with platform teams to enhance feature stores, model registries, and deployment infrastructure for AI solutions.
** Drive Technical Excellence
*** Author high-quality, well-tested, and maintainable code in Python (and/or Java).
* Contribute to shared ML frameworks, tooling, and promote engineering best practices across the research team.
* Engage in architecture discussions, design reviews, and technical roadmap development for AI initiatives.
** Mentor & Collaborate Across Teams
*** Mentor junior engineers (MLE I/II), providing code reviews, guidance, and technical leadership.
* Work closely with data scientists, software engineers, operations, and product teams to integrate ML solutions into real-world applications.
* Translate complex business and technical challenges into actionable ML solutions.
** Operate Reliable ML in a Regulated Environment
*** Ensure ML systems adhere to high standards for monitoring, alerting, security, privacy, and compliance.
* Support incident response and maintain production reliability for AI-driven systems.
* Contribute to model governance, explainability, and responsible AI practices.
** Minimum Qualifications
*** Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field (Master’s or PhD a plus).
* 6+ years of experience building and deploying machine learning systems in production environments.
* Strong proficiency in…