Ml Ops Engineer

2 weeks ago


Singapore MUNICH MANAGEMENT PTE. LTD. Full time

Artificial intelligence (AI) and advanced analytics are transforming the insurance industry across the value chain. Munich Re is at the forefront of this trend, having made a significant investment in start-of-the-art analytics infrastructure and software, central and regional analytics centers and several analytics initiatives with clients worldwide.

An exciting opportunity exists to join Munich Re's regional Life and Health analytics centre (RAC) of competence. The RAC supports Munich Re's Life and Health clients in Asia-Pacific, Middle East and Africa business. As such you will work in an agile and innovative area, gaining exposure to a variety of business problems, other teams, clients and geographies.

As a MLOps Engineer you will develop an AI technology roadmap and work with multiple internal technology partners to ensure availability of a modern AI technology platform, and associated MLOps capabilities to support operationalization (production) of AI models, related data and solution integrations into client and MR systems.

**Your job**
- Regional ML engineer in a vibrant, leading global reinsurance company with diverse data to enable innovative AI and digital solutions
- Hands-on data engineering and MLOps support to the data scientists to ensure successful deployment of AI solutions
- Play an important in the solution design and development of an AI/MLOps platform for operationalizing Munich Re AI solutions in client environments
- Oversee the AI technology roadmap for the region, ensuring synergies between existing technologies are maximized and a coherent, cost-effective technology roadmap
- Collaborate with internal technology partners and the data analytics center in Munich to leverage capabilities in analytics technology and as the team expands, potentially to manage/lead team of junior ML engineers. You will have the opportunity to work with Munich Re's leading team in underwriting and cloud technology
- Proactively research MLOps best practices and related technical architecture designs
- Design, develop, and deploy consumer-facing machine learning products
- Collaborate across Munich Re functions to create machine learning services
- Presentation of deployment solutions to internal and external stakeholders
- Networking with existing data engineering units across the globe

**Your profile**
- Postgraduate (preferably Masters or PhD) degree in computer science, computer engineering, IS, IT or similar.
- Theoretical knowledge of AI, ML and DL methods
- 3+ years' experience as a Data/DevOps engineer with a focus in deploying AI/ML solutions to production in a DevOps environment with knowledge of CI/CD pipelines (e.g., Azure DevOps)
- Experience designing machine learning platforms and data pipelines at scale
- Expertise with Kubernetes (including network security policies, certificate management, RBAC, Helm), CI/CD automation, Docker, and microservice architecture.
- Ability to write robust code for deployable services in Python
- Experience developing ETL data pipelines (using AirFlow, Azure DataFactory)
- Advanced skills in working with relational SQL data stores (Microsoft SQL, MySQL or similar) & NoSQL databases such as Cosmos DB
- Experience deploying cloud infrastructure, preferably using Azure.
- Experience of conducting UAT and knowledge of testing methodologies
- Experience in the insurance/reinsurance industry would be an advantage
- Documenting analytics deployment solution
- Explaining solution architectures and concepts to non-technical audiences and domain experts


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