Senior Staff Machine Learning Engineer

GEICO . For more information, please .Senior Staff Machine Learning Engineer page is loaded## Senior Staff Machine Learning Engineerlocations: Chevy Chase, MD: Austin, TX: Palo Alto, CA: New York City, NY: Seattle, WAtime type: Full timeposted on: Posted Todayjob requisition id: R0061884**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.**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 CareersGEICO is seeking a Senior Staff Machine Learning Engineer to help shape how Generative AI enhances customer and associate experiences across the enterprise. This is a hands-on technical role who will be leading the strategy, architecture, and delivery of ML systems for the Claims organization—designing predictive models, robust data/feature pipelines, and production-grade MLOps to drive measurable business outcomes. You will work alongside engineering teams, data scientists, and product leaders to design, build, and integrate AI-powered capabilities that automate workflows, improve decision-making, and elevate user experience. You will contribute to a culture of learning, curiosity, and innovation while growing your expertise in cutting-edge AI technologiesAbout the role* Staff+ individual contributor role focused on end-to-end ML: data and feature engineering, modeling, deployment, monitoring, and continuous improvement.* Partner with Claims Operations, Product, and Engineering to deliver ML capabilities such as severity/triage predictions, claim outcome forecasting, and automation accelerators.* GenAI (e.g., LLMs and agentic workflows) may be leveraged where it augments ML systems; strong ML depth is primary.What you’ll do* Own ML platform architecture: data/feature pipelines, experiment tracking, model registries, serving layers, offline/online evaluation, and observability.* Define standards for reliability, performance, cost efficiency, security, governance, and model risk management across ML services.* Lead design and implementation of models across classical ML and deep learning (e.g., gradient boosted trees, sequence models, Transformers for tabular/time-series/NLP where relevant).* Translate business goals into measurable ML objectives and experiment plans; ensure robust offline metrics and real-world impact.* Build scalable training and inference pipelines; establish CI/CD for ML, automated evaluations, canary releases, and rollback strategies.* Implement monitoring for data quality, drift, fairness, latency, reliability, and cost; lead incident response and postmortems.* Partner with Claims, Product, Data Science, Platform/SRE, Security, and Legal/Compliance to gather requirements, define scope, and prioritize backlogs.* Maintain pragmatic technical roadmaps balancing business outcomes, release timelines, and engineering excellence.* Own build-vs-buy decisions and tooling/service selection (speed to market, extensibility, TCO); guide platform evolution with clear architectural principles.* Lead experienced engineers through complex platform implementations; drive system-wide architectural improvements and reliability practices.* Mentor engineers and junior tech leads; codify best practices; contribute to internal documentation and promote enterprise-wide ML standards.* Where appropriate, collaborate on retrieval-augmented workflows, prompt/context management, and LLM evaluation and safety guardrails to complement ML systems.Minimum qualifications* Bachelor’s degree or above in Computer Science, Engineering, Statistics, or related field.* 10+ years of professional software development experience using at least two general-purpose languages (e.g., Java, C++, Python, C#).* 10+ years architecting, designing, and building multi-component ML platforms leveraging open-source/cloud-agnostic components: + Search/vector: ElasticSearch, Qdrant (as applicable to ML features and retrieval) + Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/Iceberg + Streaming: Kafka; plus Flink/Spark Streaming experience + Datastores: PostgreSQL; NoSQL (MongoDB, Cassandra) + Distributed compute: Spark, Ray + Workflow orchestration: Airflow, Temporal* 6+ years managing end-to-end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support.* 6+ years working with cloud providers (Azure and/or AWS) in production ML contexts.Preferred qualifications (GenAI as a plus)* Experience leveraging or fine-tuning LLMs (e.g., GPT, Llama, Mistral, Claude) to augment ML workflows, retrieval, or claims-facing tooling.* Hands-on with MLOps tooling: MLflow/Kubeflow, model registries, feature stores (e.g., Feast), experiment tracking, A/B testing and online evaluation frameworks.* Observability: Prometheus/Grafana, OpenTelemetry; SLO-driven operations and incident management.* Model safety, fairness, explainability (e.g., SHAP/LIME), and regulatory compliance; familiarity with model risk management practices.* Insurance/financial services domain experience: claims automation, fraud detection, risk modeling, subrogation, severity/triage, and regulatory stewardship.* Experience with high-throughput, low-latency inference and real-time feature pipelines.#LI-JK1**Annual Salary**$150,000.00 - $300,000.00The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.**The GEICO Pledge:****Great Company:** At GEICO, we help our customers through life’s twists and turns. Our mission is to protect people when they need it most and we’re constantly evolving to stay ahead of their needs.We’re an iconic brand that thrives on innovation, exceeding our customers’ expectations and enabling our collective success. From day one, you’ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people’s lives.**Great Careers:** We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career – and your potential – in mind. You’ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.**Great Culture:** We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are #J-18808-Ljbffr