Job Description

Join to apply for the Senior Machine Learning Engineer I role at QBE North America Join to apply for the Senior Machine Learning Engineer I role at QBE North America Get AI-powered advice on this job and more exclusive features. The Opportunity: At QBE, we believe machine learning and AI can significantly improve how insurance works for everyone. We’re looking for a curious and motivated Senior Machine Learning Engineer I to help us build and deploy real-world ML and AI solutions that support our Pricing, Underwriting, and Claims teams. This role is ideal for someone early in their ML engineering journey who wants to build their skills while contributing to meaningful projects. You’ll work closely with experienced engineers and data scientists, applying best practices in software engineering and machine learning to deliver reliable, production-ready systems. Location: Sun Prairie, WI highly preferred, but will consider any of our office locations (New York, Atlanta, Chicago) or possibly remote for the right candidate Work Arrangement: This role is ideally a hybrid role, requiring 2-3 days/week in the office, though fully remote may be a consideration for the right candidate The starting salary range for this role is between $88,000-$165,000 Primary Details Time Type: Full time Worker Type: Employee The Opportunity: At QBE, we believe machine learning and AI can significantly improve how insurance works for everyone. We’re looking for a curious and motivated Senior Machine Learning Engineer I to help us build and deploy real-world ML and AI solutions that support our Pricing, Underwriting, and Claims teams. This role is ideal for someone early in their ML engineering journey who wants to build their skills while contributing to meaningful projects. You’ll work closely with experienced engineers and data scientists, applying best practices in software engineering and machine learning to deliver reliable, production-ready systems. Location: Sun Prairie, WI highly preferred, but will consider any of our office locations (New York, Atlanta, Chicago) or possibly remote for the right candidate Work Arrangement: This role is ideally a hybrid role, requiring 2-3 days/week in the office, though fully remote may be a consideration for the right candidate The starting salary range for this role is between $88,000-$165,000 Your New Role: Design, build, and deploy machine learning models that solve practical business problems in Pricing, Underwriting, and Claims. Collaborate with ML engineers, data scientists, and business stakeholders to translate requirements into well-scoped technical solutions. Contribute to the development and maintenance of deployment pipelines, ensuring models are robust, reproducible, and scalable. Write clean, efficient, and well-documented Python code using tools like pandas, numpy, and pydantic. Participate in code reviews, testing, and validation to ensure model quality and reliability in production. Learn and apply modern ML tools and frameworks such as Transformers and MLflow. Engage in team discussions with a growth mindset, sharing ideas, asking questions, and learning from feedback. Required Qualifications: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field - or equivalent practical experience. 2+ years of experience in software engineering, data science, or machine learning roles. Preferred Skills And Experience Proficiency in Python and familiarity with core data science libraries (e.g., pandas, numpy, polars, scikit-learn). Hands-on experience with Azure. Understanding of MLOps concepts such as version control (Git), CI/CD, and containerization (Docker). Experience with model validation, monitoring, and performance tracking. Familiarity with software engineering best practices, including unit testing and clean code principles. Experience working with DevOps pipelines for automating ML workflows and deployments. Familiarity with Infrastructure as Code (IaC) using Terraform to manage cloud resources. Strong communication and collaboration skills; comfortable working in a team environment. Eagerness to learn and improve continuously - technically and professionally. Compensation Package: The salary range for this role is provided above. This is the national range for location(s) listed. The salary offer will be decided based on the role's complexity, its location, and the candidate’s professional background, including their education and experience. Beyond the base salary, regular full-time and part-time employees will also be eligible for QBE’s annual discretionary bonus plan based on business and individual performance. We encourage all candidates to apply, even if their salary expectations fall outside of this range, as we are committed to finding the right fit for our team. QBE Benefits: We offer a range of benefits to help provide holistic support for your work life, whatever your circumstances. As a QBE employee you will have access to: Hybrid Working – a mix of working from home and in the office 22 weeks of paid leave for family growth, with 12 weeks available to all parents on a gender-equal basis Competitive 401(k) program with company match up to 8% Well-being program including holistic wellbeing coaching, gym membership, confidential counselling, financial and legal advice Tuition Reimbursement for professional certifications, and continuing education Employee Network and Community – QBE actively supports six Employee Networks, and many ways to give back to your community To learn more, click here: Benefits | QBE US . Why QBE? What if you could have a positive impact – at work and in the world? At QBE, we’re enabling a more resilient future – for our customers, communities, environment, and for our people. We’re building momentum to achieve something significant and know our people are at the center of our success. Our industry offers interesting and varied careers where you can help people to protect what matters most. As part of the QBE team, you’ll get to spend every day working with people who are passionate, talented and kind. And our international scale means we’re big enough for your ambitions, yet small enough for you to make a real impact. Join us now, so you can be part of our success – and we can be part of yours! Commitment to Diversity QBE is committed to providing reasonable accommodation to, among others, individuals with disabilities and disabled veterans. If you need an accommodation because of a disability to search and apply for a career opportunity with QBE, please inform our Talent Acquisition team to let us know the nature of your accommodation request and your contact information. Equal Employment Opportunity: QBE provides equal employment opportunities to applicants and employees without regard to race; color; gender; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; protected veteran status; or disability or any other legally protected status. Supplementary information Skills: Communication, Critical Thinking, Data Science, Data Visualization, Financial Products, Intentional collaboration, Machine Learning, Managing performance, Mentorship, Research Analysis, Risk Management, Scrum (Agile), Stakeholder Management, Strategic Leadership, Team Management How to Apply: To submit your application, click "Apply" and follow the step by step process. Equal Employment Opportunity: QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Insurance Referrals increase your chances of interviewing at QBE North America by 2x Sign in to set job alerts for “Machine Learning Engineer” roles. 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