Senior ML Engineer, Generative AI

🕒 April 21

🇺🇸 United States – Remote

💵 $160k - $240k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

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

• Lead the design, implementation, and evolution of Guidewire’s GenAI and LLM products, including data ingestion, feature pipelines, model training, fine-tuning, deployment, and monitoring on AWS (e.g., S3, EC2, RDS, SageMaker). • Architect and build robust ML/LLM pipelines that power high-impact use cases such as claim summarization, underwriting assistance, pricing and rating intelligence, and developer productivity tools across our product portfolio. • Develop and optimize LLM solutions using techniques such as prompt engineering, retrieval-augmented generation (RAG), vector databases, and fine-tuning to deliver reliable, safe, and high-performing experiences for insurance users. • Collaborate with Product Strategy, PDO, and Professional Services teams to align GenAI capabilities with the broader Product VPMOM, Agentic AI product roadmap, and customer adoption goals (including Claims Summary, Underwriting Assistant, Codelift, and other GenAI “lifts”). • Establish and apply ML Ops best practices for CI/CD, experimentation, evaluation, observability, and responsible AI, ensuring models are auditable, secure, and production-ready at scale. • Mentor and coach engineers and data scientists, conduct code and design reviews, and champion technical excellence, including performance, reliability, and cost efficiency of AI workloads. • Partner with cross-functional teams (Security, Finance, BizTech, GTM) to ensure AI solutions adhere to data governance and security controls, and contribute to Guidewire’s mission to transform how P&C insurers do business through cloud, analytics, and AI.

🎯 Requirements

• 5+ years of professional experience in Machine Learning and/or Data Science, including end-to-end delivery of production ML systems. • Deep expertise in Python and experience building scalable ML/LLM services and pipelines, ideally on AWS using services such as S3, EC2, RDS, and SageMaker. • Strong understanding of ML Ops practices for model development, deployment, monitoring, and lifecycle management (including CI/CD for ML, experiment tracking, model registries, and drift detection). • Hands-on experience with classical and gradient-boosting models (such as GLM, Random Forest, and XGBoost) and their application to real-world business problems. • Deep understanding of neural networks and transformer-based architectures for LLMs and chat models, including familiarity with open-source foundation models and their fine-tuning and inference. • Experience with prompt engineering, RAG and related LLM architecture patterns, and vector databases for semantic search and retrieval. • Solid knowledge of evaluating and monitoring LLM performance using NLP and LLM-assisted metrics, with a focus on safety, robustness, and user experience. • Demonstrated technical leadership: driving design decisions, leading complex engineering efforts, mentoring peers, and conducting thoughtful code and architecture reviews.

🏖️ 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.