Responsibilities
- Architect and/or 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
- 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
Requirements
- 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, data pipeline, data engineering and data pre-processing
- Foundational knowledge of data visualization tools such as Tableau, Qlik Sense, Power BI
- Agile and Scrum experience is preferred
- Practical experience of software engineering or software development experience in making AI/ML models production ready , experience in developing, implementing and maintaining IT systems
