Staff /Senior Machine Learning Engineer, Guidewire

• Bachelor’s or Master’s Degree in Computer Science, or equivalent level of demonstrable professional competency
• 5+ years of professional experience working in Machine Learning and Data Science
• Demonstrated leadership experience on technical projects
• Experience conducting code reviews and being a coach and mentor to other developers
• Knowledge of ML Ops good practices for model development, deployment and monitoring
• Expert in Python programming language
• A strong understanding of AWS cloud technologies such as S3, EC2, RDS, etc
• Experience developing model pipelines using AWS Sagemaker
• Experience using statistical learning algorithms such as GLM, XGBoost, and Random Forest to solve real world business problems
• Deep understanding of neural network and transformer algorithms for large language and chat models
• Familiarity with the setup and use of various open source LLM foundation models
• Prompt engineering and fine tuning concepts for LLM performance
• Creating and using vectorized databases for data storage and retrieval
• Familiarity with various LLM architecture patterns such as RAG and FLARE
• Understanding of LLM performance evaluation and monitoring using NLP and LLM-assisted metrics

Desirable

• Be a technical leader for a cross-functional team implementing Generative AI (GenAI) solutions for some of the most critical business needs in the insurance industry
• You will be a primary stakeholder and key developer for the complete end-to-end GenAI platform at Guidewire. Design, test and build GenAI infrastructure for guidewire Large Language Models (LLMs). Creating data solutions, prompt engineering for models, fine tuning and deploying LLMs
• This role is a great opportunity for individuals motivated by learning cutting edge technologies and their application to solve real world business problems
• Guidewire is the AWS for insurance companies that use our platforms and applications
• The GenAI solutions developed by you and this team will be used by hundreds of insurance companies and impact billions of dollars in annual transactions