GEICO is seeking a Senior Machine Learning Engineer, Fraud Risk Modeling in Palo Alto, CA (onsite). In this role, you will lead the design, implementation, and deployment of production-grade machine learning models, with opportunities to build scalable ML infrastructure and own end-to-end model lifecycle management. GEICO provides competitive pay and a supportive environment focused on growth, mentorship, and certification assistance.
What you’ll do
- Lead model design and implementation, partnering with Product, Business Units, and Engineering teams on fraud risk modeling solutions.
- Build scalable ML infrastructure for model training, automated hyperparameter tuning, and deployment pipelines that stay reliable and performant at scale.
- Develop production-grade ML services and APIs, writing modular and reusable code that turns models into deployable components for future projects.
- Optimize model performance by debugging and troubleshooting issues, tracking key metrics, and improving reliability, speed, and efficiency in production.
- Own the full ML lifecycle, including monitoring, retraining, and version management to keep models aligned with business needs over time.
- Provide leadership and mentorship to junior machine learning engineers, promoting best practices across software engineering, model development, and deployment.
- Collaborate across teams such as data engineering, software development, and product management to integrate models and support smooth production operations.
- Stay current with industry trends by exploring new techniques and system engineering tools to advance team practices in machine learning and systems architecture.
What you bring
- B.Sc. in Computer Science, Machine Learning, Engineering, or a related technical field.
- 6+ years of hands-on experience applying machine learning techniques, including deep learning, reinforcement learning, and NLP in production environments.
- 6+ years using open-source and/or cloud-agnostic components such as Snowflake, Kafka, PostgreSQL, MongoDB, Cassandra, Spark, Ray, Airflow, and Temporal.
- 6+ years professional software development experience with at least two general-purpose languages, such as Java, C++, Python, or C#.
- 6+ years with machine learning frameworks including TensorFlow, PyTorch, and Scikit-learn.
- At least 4 years with cloud platforms (AWS, Azure, GCP) and containerization (Docker), plus orchestration with Kubernetes.
- Proven experience deploying ML models in production with scalability, reliability, and high availability in mind.
- Strong engineering fundamentals: object-oriented design, design patterns, clean maintainable code, Git, and familiarity with Agile.
- Distributed systems expertise for scaling ML models in production, including distributed data processing and microservices architectures.
- Experience with MLOps such as CI/CD, automated testing, and deployment pipelines for ML models.
- System architecture and performance optimization, including designing fault-tolerant systems for large-scale data and high-volume requests.
- Experience deploying on AWS/Azure/GCP and familiarity with AWS SageMaker, GCP AI Platform, and Azure Machine Learning.
- Monitoring and logging experience to track performance and ensure efficient resource utilization.
Helpful background (preferred)
- 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 or managed services for ML model deployment.
- Advanced degree (M.Sc., Ph.D.) in a related field.
- Experience with GPU/TPU optimization for accelerated training and inference.
Tools you may work with
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
Compensation and GEICO pledge
Annual salary: $115,000.00 - $230,000.00
- Great Company: Protecting customers through life’s twists and turns with 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 to support your well-being and future.
Benefits
- Competitive pay, benefits, and flexibility to support your well-being and future.
- Personalized development programs, mentorship, and certification assistance.
