Senior Machine Learning Engineer

Responsibilities

• check_circle Build and support ML lifecycle tooling for model deployment, monitoring, and alerting
• check_circle Maintain and improve the Kubeflow environment for Data Scientists and Actuaries
• check_circle Create pricing analytics tools to accelerate impact analysis and reduce manual work
• check_circle Collaborate with pricing and product teams to deliver high-impact tooling
• check_circle Communicate complex concepts clearly to technical and non-technical audiences

Basic qualifications

• Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science, or a related field
• Strong experience managing the full ML model lifecycle (batch and online)
• Solid understanding of statistical methods, including GLMs and modern ML techniques
• Proven ability to build and deploy production-quality Python applications (pandas, scikit-learn)
• Experience with DevOps and ML tooling, including Kubernetes, Docker, CI/CD, and git-based workflows
• Familiarity with cloud platforms (AWS) and cloud data warehouses (Snowflake/SQL)

Benefits