Senior Machine Learning Engineer, Fraud Risk Modeling

GEICO is hiring a Senior Machine Learning Engineer for fraud risk modeling to lead the end-to-end creation and production deployment of machine learning solutions.

Responsibilities

• Lead design and implementation of machine learning models, coordinating with Product, Business Units, and Engineering teams
• Build scalable ML infrastructure for model training, automated hyperparameter tuning, and deployment pipelines
• Write production-grade code to deliver machine learning services and APIs, keeping modules reusable for future projects
• Debug and troubleshoot model performance in production; track key metrics and improve reliability, speed, and efficiency
• Own end-to-end model lifecycle management, including monitoring, retraining, and model version management
• Provide leadership and mentorship to junior machine learning engineers and promote best practices for software engineering, model development, and deployment
• Collaborate across teams such as data engineering, software development, and product management to integrate models into production systems
• Stay current on new machine learning techniques and system engineering tools and apply them to team processes and architecture

Requirements

• B.Sc. in Computer Science, Machine Learning, Engineering, or a related technical field
• 6+ years of hands-on experience applying machine learning techniques in production, including deep learning, reinforcement learning, and NLP
• 6+ years using open-source and/or cloud-agnostic components, including data warehouse (e.g., Snowflake), streaming (e.g., Kafka), relational databases (e.g., PostgreSQL), NoSQL (e.g., MongoDB, Cassandra), distributed processing (e.g., Spark, Ray), and workflow management (e.g., Airflow, Temporal)
• 6+ years of professional software development experience using at least two general-purpose languages such as Java, C++, Python, or C#
• 6+ years of experience with machine learning frameworks including TensorFlow, PyTorch, and Scikit-learn
• At least 4 years of experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker), plus orchestration tools such as Kubernetes
• Proven experience deploying machine learning models in production with scalability, reliability, and high availability
• Strong object-oriented design and design patterns; ability to write clean, maintainable code; proficiency with Git and familiarity with Agile methodologies
• Solid understanding of distributed systems and scaling machine learning in production, including distributed data processing and microservices architectures
• Expertise implementing MLOps practices such as CI/CD, automated testing, and automated deployment pipelines for ML models
• Strong system architecture and performance optimization skills, including designing fault-tolerant systems for large-scale data and high-volume requests
• Experience deploying ML models in cloud environments such as AWS, Azure, or Google Cloud, with familiarity in AWS SageMaker, GCP AI Platform, or Azure Machine Learning
• Experience setting up monitoring and logging to track production performance and efficient resource utilization

Preferred Qualifications

• Experience designing and building high-performance distributed systems for large-scale data ingestion and processing for ML workloads
• Experience with real-time inference pipelines and low-latency model serving
• Familiarity with serverless computing or managed services for ML deployment
• Advanced degree (M.Sc., Ph.D.) in a related field
• Experience with GPU/TPU optimization for accelerated model training and inference

Technologies

• Java, C++, Python, C#, TensorFlow, PyTorch, Scikit-learn
• AWS, Azure, GCP
• Docker, Kubernetes
• Snowflake, Kafka, PostgreSQL, MongoDB, Cassandra, Spark, Ray
• Airflow, Temporal, Git
• AWS SageMaker, GCP AI Platform, Azure Machine Learning

Benefits

• Competitive pay, benefits, and flexibility to support well-being and future needs
• Personalized development programs, mentorship, and certification assistance

• Location: Palo Alto, CA (onsite)
• Annual salary: USD 115,000 - 230,000

GEICO Pledge: Great Company (innovation and integrity), Great Careers (personalized development programs, mentorship, and certification assistance), Great Culture (inclusive and collaborative culture rooted in shared success), Great Rewards (competitive pay, benefits, and flexibility).