- Develop and manage backend systems for data and machine learning products
- Develop, deploy and manage customer-oriented database systems based on customer requirements and data
- Develop application servers for data visualization
- Deploy and manage cloud-based system, especially AWS EC2 and S3
- Collaborate with engineering teams to design and implement software solutions for scientific problems
- Develop a backend platform for advanced MLOps
- Develop a machine-learning pipeline
- Implement machine learning algorithms
- Develop a high-level framework for Pipeline Dev automation
- Experience in building large-scale products
- Hands-on experience in developing API-based environments such as RESTful API, GraphQL, etc.
- Experience in developing and managing API gateways
- Experience in on-premise and cloud environment architecture and operations
- Understanding of container and orchestration technologies, such as Docker and Kubernetes
- Experience in version control systems and collaboration tools such as Confluence, Notion, Jira, Git, etc.
- Hands-on experience in Ubuntu or Alpine Linux
- Hands-on experience in IaC(Infrastructure as Code) such as Terraform, Pulumi, and automation
- Hands-on experience in backend development using Python, node.js, Golang, gRPC, Rust and related frameworks
- Hands-on experience in DataOps or MLOps development and operations
- Hands-on experiences in eBPF, Cilium, or Observability
- Email your resume to firstname.lastname@example.org
- Use the following email title format:
[Application] (REC-year-num) Your_Name
[Application] (REC-2023-08) John_Wick.
- Make sure that your application code (
REC-year-num) is correct.
- Attach your resume in PDF format.
- Feel free to include any necessary information in your resume. However, be concise and to the point.
- Application (접수): 2023/09/18 ~ 2023/10/08
- Screening (서류심사): ~ 10/11
- Online interview (온라인인터뷰): 10/16 ~ 10/20
- Onsite interview (현장면접): 10/23 ~ 10/27
- Decision (결과): ~ 10/31