ML Platform Engineer

About This Role

This ML Platform Engineer role involves building and evolving the infrastructure that enables machine learning teams to develop, deploy, and operate models efficiently. You will work closely with Data Scientists, Data Engineers, MLOps engineers, and Product Engineering teams to build reliable, secure, and scalable ML platform capabilities.

Responsibilities

• Design, develop, and maintain components of a scalable and secure ML platform supporting the machine learning lifecycle, from data ingestion and model training to deployment and monitoring
• Build infrastructure for model training, experiment tracking, hyperparameter tuning, and model registry using tools such as MLflow, Kubeflow, Sage Maker, Vertex AI, or similar technologies
• Develop and maintain automated ML workflows and CI/CD pipelines for machine learning applications
• Collaborate with Data Scientists and Data Engineers to build reliable, model-ready datasets and improve the ML development experience
• Help optimize ML workloads across cloud infrastructure, compute, and storage to improve scalability and efficiency
• Contribute to platform reliability by implementing monitoring, logging, testing, and operational best practices
• Participate in design discussions, code reviews, and technical planning while contributing to engineering best practices
• Ensure platform components meet security, privacy, and compliance requirements
• Deliver core ML platform capabilities that improve the productivity of machine learning teams
• Collaborate with cross-functional teams to build scalable, reliable, and secure ML infrastructure
• Contribute to automation, operational excellence, and engineering best practices across the ML platform
• Help improve the developer experience for building, deploying, and managing machine learning models
• Support Guidewire's AI initiatives by delivering robust platform capabilities that enable teams to build and operate ML solutions efficiently

Requirements

• Demonstrated ability to embrace AI and apply it in day-to-day engineering work to improve productivity and software quality
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
• 3+ years of software engineering experience, including experience building or supporting ML platforms, data platforms, or cloud-native applications
• Strong programming skills in Python, Go, or Java
• Experience with Docker and Kubernetes or similar container orchestration technologies
• Familiarity with MLOps tools such as MLflow, Kubeflow, Sage Maker, Vertex AI, or Databricks
• Experience working with cloud platforms such as AWS, Azure, or GCP
• Basic understanding of machine learning workflows and common algorithms
• Strong communication, collaboration, and problem-solving skills

Nice to have:

• Experience deploying and monitoring machine learning models in production
• Familiarity with feature stores, workflow orchestration tools (Airflow, Argo), or model monitoring solutions
• Exposure to streaming technologies such as Kafka or Spark
• Experience with Infrastructure as Code and CI/CD tools such as Terraform and Team City
• Familiarity with ML governance, reproducibility, and model lifecycle management
• Experience in the insurance, financial services, or another regulated industry

Benefits

• Health, dental, and vision insurance
• Paid time off
• Company sponsored retirement plan
• Annual company bonus plan, commissions, and/or long term incentive awards (contingent on a variety of factors including, but not limited to, company and employee performance)

About the Company

Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently. The company combines digital, core, analytics, and AI to deliver its platform as a cloud solution.