Guidewire

Overview

Architect and scale the ML platform for data scientists and ML engineers that powers Guidewire’s next-generation products in a hybrid work environment.

About Guidewire

Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently. We combine digital, core, analytics, and AI to deliver our platform as a cloud service.

Requirements & Eligibility

• 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 statistical learning algorithms (GLM, XGBoost, Random Forest) and deep learning.

Key Responsibilities

• Architect and guide the design of a scalable, secure ML platform supporting the full ML lifecycle.
• 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.
• 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.