Senior/Staff Machine Learning Engineer

Summary

Your day-to-day:
Be part of 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 workflow 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 GenAI solutions.

Guidewire’s GenAI team is the center of excellence for machine learning and AI. 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.

Job Description

Requirements:

• 7 plus years of professional experience working in Machine Learning and Data Science.
• Bachelor’s or Master’s Degree in Computer Science, or equivalent level of demonstrable professional competency.
• 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.

Preferred Skills:

• Data engineering experience with SQL, Spark or AWS Glue.
• Experience using Docker or Kubernetes to deploy containerized applications.
• Creating API services for backend application functionality.
• Experience using TeamCity and Terraform for infrastructure setup and CI/CD.
• Insurance industry or related experience such as banking and finance

The US base salary range for this full-time position is $176,000 - $308,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Disability Accommodations and Guidewire’s Appeals Process. Guidewire provides accommodations to the hiring process to create a fair opportunity for candidates with disabilities to contend for open positions. Accommodation requests should be directed to Accommodations@guidewire.com. If things do not go as hoped, we invite you to use our appeals process. Guidewire promises to independently review any denied accommodation and any decision not to offer you the position. The appeals process is the same in either case. Within five business days of receiving a notice of denial of an accommodation, or receiving a notice of your non-selection for a vacancy, e-mail Accommodations@guidewire.com to make an appeal. Guidewire will assign a new decision-maker to review the request and/or hiring decision, who will then notify you in writing of a decision within 10 business days.

About Guidewire

Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently. We combine digital, core, analytics, and AI to deliver our platform as a cloud s