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.

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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

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