Responsibilities:
- To handle infrastructure set-up, Cloud engineering and deployment of AI/machine learning models in the MLOps platform.
- Review technical solutions for the deployment of AI models, along with the data pipelines and visualization interfaces.
- Utilize DevOps tools and automate model deployment / tuning via orchestration.
- Provide guidance for maintenance, support and enhancements to model deployment platforms.
- Hands-on experience to:
- Analyze, design and develop test for model deployment and automation.
- Design and implement API interfaces.
- Set up Continuous Integration / Continuous Deployment pipeline.
- Work with Data Scientists on understanding and enhancing data models for deployment.
- Liaise with Data Engineers on the requirements for each data sources, understand the ETL required.
- Work with DBA to manage the DB servers.
- Work with Cloud infra engineers for on-boarding to AWS and MS Azure.
Requirement:
- At least 5 years’ experience in developing, implementing and maintaining IT systems.
- Degree and equivalent training (e.g. specialist diploma, professional certificate) in Business Analytics, Computer Science / Computer Engineering, Computer Engineering, Information Systems, Mathematics, Statistics, Engineering or related disciplines that possesses an analytical component.
- Practical experience of software engineering or software development experience in making AI/ML models production ready.
- Understanding of programming language such as Python, R and SQL.
- Foundational knowledge of Cloud computing and infrastructure setup.
- Foundational knowledge of data pipeline, data engineering and data pre-processing.
- Foundational knowledge of data visualization tools such as Tableau, QlikSense, Power BI.
- Agile and Scrum experience is preferred.
