Machine Learning Engineer – III

2 days ago

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

💵 $128k - $192k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

Apply Now

Receive Emails with Similar Jobs

Guidewire Software

WebsiteLinkedInAll Job Openings

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.

1001 - 5000 employees

Founded 2001

💰 $750k Series C on 2008-03

📋 Description

• Be part of a cross-functional team implementing Machine Learning (ML) 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 ML Ops lifecycle at Guidewire. • Design, test and build infrastructure for Guidewire AI and ML models. • Creating data solutions, developing automated systems, and deploying AI and ML models. • Guidewire’s ML Engineering team is the center of excellence for machine learning and AI.

🎯 Requirements

• 3+ 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 Docker or Kubernetes to deploy containerized applications. • Proficiency in building ML Infrastructure with IaC tools to support large ML workloads. • Experience using statistical learning algorithms such as GLM, XGBoost, and Random Forest to solve real world business problems. • Deep understanding of statistical learning methods and how to evaluate models for performance in a production setting. • Familiarity with the setup and use of various open source LLM foundation models. • Prompt engineering and fine tuning concepts for LLM performance.

🏖️ Benefits

• Health insurance • Dental insurance • Vision insurance • Paid time off • Company sponsored retirement plan • Eligibility for the annual company bonus plan