Senior Machine Learning Platform Engineer

Summary Join Guidewire’s Product Development & Operations (PDO) team, where we deliver operational excellence and transformative innovation for the world’s leading P&C insurance software. Our team is at the forefront of AI, cloud, and data platform adoption, working collaboratively in a hybrid environment to ensure secure, scalable, and efficient solutions. We thrive on curiosity, continuous improvement, and a culture that values diverse perspectives and teamwork. ¹ As a Senior AI/ML Platform Engineer, you will architect and scale the ML platform for data scientists and ML engineers that powers Guidewire’s next-generation products. This is a high-impact role for a technical leader passionate about distributed systems, MLOps, and empowering data-driven innovation. You will help shape the future of insurance technology by enabling seamless ML workflows and accelerating the adoption of AI across Guidewire’s solutions. Job Description High-priority opening — we’re moving fast and looking to hire ASAP. What you’ll do Architect and guide the design of a scalable, secure ML platform supporting the full ML lifecycle, from data ingestion to model monitoring. Design and implement infrastructure for model training, hyperparameter tuning, experiment tracking, and model registry. Orchestrate ML workflows using tools such as Kubeflow, SageMaker, MLflow, or similar. Collaborate with Data Scientists, MLOps engineers, Data Engineers, and Product Engineering to define best practices for reproducibility, governance, and CI/CD for ML. Partner with Data Engineers to build robust data pipelines for model-ready datasets. Optimize ML workload performance across compute and storage layers using cloud-native and open-source solutions. Lead technical discussions, mentor junior engineers, and help set the technical vision for the ML platform roadmap. Ensure compliance with security, privacy, and regulatory requirements throughout the ML lifecycle. At Guidewire, we foster a culture of curiosity, innovation, and responsible use of AI—empowering our teams to continuously leverage emerging technologies and data-driven insights to enhance productivity and outcomes. What you’ll bring Required Demonstrated ability to embrace AI and apply it to your current role as well as data-driven insights to drive innovation, productivity, and continuous improvement. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 10+ years of software engineering experience, including 5+ years working on ML platforms or infrastructure. Expertise in building large-scale distributed systems and microservices. Strong programming skills in Python, Go, or Java. Experience with containerization and orchestration (e.g., Docker, Kubernetes). Advanced experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks. Cloud platform experience (AWS, GCP, or Azure). Experience with…