Location
Bangalore | India
Job description
The Data Platform Engineering & Operations team deals with data & analytics platforms for enabling the creation of innovative solutions to data driven business needs. It also enables Swiss Re Group to efficiently utilize the platforms and ensures their availability and proper functioning.
The Opportunity
Interested in joining Swiss Re's endeavors to become a truly data-driven risk company? We are the GDS Data Platform Engineering & Operations team. We own and serve data analytics and data science tools to a large company-internal user base. We set up and maintain cloud-based PaaS and SaaS solutions with a focus on big data processing, analytics, ML & AI, and large language models. Staying in touch with our users continuously we strive to anticipate emerging client needs, provide responses to user inquiries, and solve their issues. We enable our users in their adoption of MLOps and more recently also LLMOps best practices. While we are aiming to provide a high-quality service to our clients, our systems must remain both secure and cost effective.
As our new colleague you will operate in an agile environment working in tight cooperation with peers, internal experts, and business clients to support, organize and manage various activities within the team.
What you will work on during your first year at Swiss Re:
- Your primary responsibility will involve the setup, configuration, and ongoing maintenance of Azure PaaS (Platform as a Service) and SaaS (Software as a Service) components, ensuring optimal functionality and system reliability.
- A significant part of your role will be dedicated to designing and constructing robust production Model (Machine Learning/Large Language Models) deployment pipelines within the public cloud environment. This will involve creating and refining model monitoring scripts and intuitive dashboards to track and report on model performance.
- You will be expected to conduct thorough and continuous analysis of the ML/LLM pipeline, deployment processes, and monitoring scripts. This will enable you to define necessary updates and modifications to accommodate changes in applications, data, or model structures effectively.
- One of your key contributions will be to the development and implementation of DevSecOps best practices focused around our large language model operations (LLMOps). This will entail devising strategies to improve security and operational efficiency in our model development and deployment processes.
- You will support our large internal customer base of data scientists, ML engineers and actuaries to make use of Azure ML, Azure OpenAI & Open Source LLMs.
- To establish new services, you will provide technical and non-technical information to our Digital Governance Framework team to obtain their approval sign offs.
- You will help other teams to achieve their own project goals using the tools provided by the team.
- Drive efficiencies in products and processes: capacity planning, configuration management, performance tuning, monitoring, backup/restore and root cause analysis.
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