Join Guidewire’s Product Strategy team, where we drive operational excellence and transformative innovation by embedding AI and GenAI across our product portfolio. Our mission is to deliver secure, scalable, and efficient solutions that create measurable value for customers, with a collaborative, agile, and customer-centric culture. You’ll work alongside passionate colleagues who blend insurance expertise with data science to shape the future of P&C insurance technology. As a Senior Machine Learning Engineer, you will play a pivotal role in accelerating AI adoption and launching new, market-ready solutions. We are seeking a creative, analytical problem solver with deep expertise in ML and LLMs, who thrives in a fast-paced, evolving environment. Your work will directly impact Guidewire’s mission to deliver innovative, customer-focused products and support our ambitious growth and operational goals. Job Description What you’ll do Deliver AI/ML models from initial planning through data sourcing, preparation, model building, training, and deployment in Guidewire’s cloud environment, with a focus on leveraging open source models. Create AI-based prototypes to evaluate model and design options, collaborating with internal stakeholders to analyze quality and relevance of results. Train and tune models to optimize algorithmic outcomes and ensure robust, production-ready solutions. Integrate models into production systems, partnering with Engineering to embed AI into product architecture. Work cross-functionally to understand product needs and scope innovative AI solutions that address evolving customer requirements. Conduct research into emerging AI models and technologies, staying connected to industry trends and best practices. Contribute to Guidewire’s wider mission by supporting operational excellence, transformative innovation, and customer-centricity in every project. 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.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
501-1,000 employees