- Manage Kubernetes based production infrastructure on Azure supporting multiple machine learning and data focused services
- Implement CI/CD pipelines using Azure Devops with a focus on testing, code quality, and security
- Production monitoring, alerting, and incident management
- Collaborate on projects with a team of data scientists and engineers
- Adapt and customize machine learning and natural language processing to execute core data ingestion and transformation tasks: translations, validations, exception detection. Work with both commercial software solutions and open source software
- Run distributed image recognition and natural language processing to capture data from unstructured data including image, text and handwriting
- Implement Python-based predictive models and applications as microservices using the Flask web framework
- Advocate for software engineering best practices, perform code review, and facilitate collaboration
- Evaluate statistical, machine learning and deep learning methods and technologies that could offer potential competitive advantages
- Collaborate with members of the Munich Re global community and external partners in client organization
First and foremost, the successful candidate will demonstrate a natural desire to provide exceptional client service through his/her energy, enthusiasm and initiative.
In addition, we are looking for the following qualifications:
- Post-secondary degree in Computer Science, Statistics, Mathematics, Information Technology, Engineering, equivalent field or substantial coursework in relevant disciplines.
- 3-5 years of experience as a DevOps engineer, Sofware Engineer or Data Engineer.
- Experience deploying cloud infrastructure, preferably using Azure.
- Expertise with Kubernetes (including network security policies, certificate management, RBAC, Helm), CI/CD automation, Docker, and microservice architecture.
- Experience with Python, Flask, SQL.
- The ability to learn quickly.
- A drive to make a difference.
- Thrive in a dynamic environment and successfully deliver on multiple assignments under deadlines.
- Insurance or financial services background is preferred but not required.
- Familiarity with big data technologies (ex. Apache Spark, Airflow, etc), natural language processing and deep learning frameworks (ex. Tensorflow, Pytorch) is an asset but not required.
- Familiarity with Infrastructure-as-code (Terraform, Anisible, etc) is preferred.