Senior Machine Learning Platform Engineer

🕒 December 24, 2025

🇺🇸 United States – Remote

💵 $148k - $222k / year

⏰ Full Time

🟠 Senior

🏗️ Platform Engineer

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Guidewire Software

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2001

💰 $750k Series C on 2008-03

Software • Insurance • Cloud Computing

Guidewire Software is a leading provider of software solutions for the property and casualty (P&C) insurance industry. The company offers a comprehensive platform that includes core applications such as PolicyCenter, ClaimCenter, and BillingCenter, as well as advanced analytics and a robust cloud platform. Guidewire focuses on delivering digital transformations, improving operational efficiencies, and enhancing customer service for insurers globally. Through collaborations and partnerships, Guidewire supports a wide range of insurance products and services, including usage-based and embedded insurance. With its commitment to innovation and customer success, Guidewire continues to empower insurers to meet the evolving demands of the industry.

📋 Description

• 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.

🎯 Requirements

• 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). • Familiarity 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 (neural networks, transformers). • Strong communication, leadership, and problem-solving skills.

🏖️ Benefits

• Flexible work environment • Health and wellness benefits • Paid time off programs, including volunteer time off • Market-competitive pay and incentive programs • Continual development and internal career growth opportunities