AI & Cloud Infra Software Engineer (Fresh Grad)
Bitdeer offers cloud computing and AI cloud services with a focus on high-performance computing and data center management.
Funding
About Bitdeer
Bitdeer is a high-performance computing platform that provides cloud service solutions, including AI cloud instances, cloud computing, and data center management. It offers a range of services aimed at simplifying the deployment and management of GPU computing instances, cloud hosting, and hash rate markets for mining. Bitdeer's platform is designed to support users from start to finish, offering superior networking, exceptional GPU computing, and comprehensive AI toolkits for enterprise AI success.
Skills
About the Role
You will design and build distributed systems that power cluster management, scheduling, and resource allocation for large-scale AI workloads. You'll develop infrastructure platforms supporting AI training and inference, working across container orchestration, cluster scheduling, and workload isolation. You'll optimize performance across compute, networking, and storage layers, and build automation tools for infrastructure provisioning using Infrastructure as Code practices. You'll partner closely with hardware, networking, and ML teams to deliver end-to-end infrastructure solutions at hyperscale.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related technical field from top universities
- 0 to 2 years of working experience in related fields
- Strong programming skills in at least one of: Go, C++, Python, or Rust
- Solid understanding of data structures and algorithms
- Solid understanding of operating systems fundamentals
- Solid understanding of computer networks (TCP/IP, distributed systems basics)
- Interest in AI Infrastructure, high-performance computing (HPC) and cloud systems
Responsibilities
- Design and build distributed systems for cluster management, scheduling, and resource allocation
- Develop infrastructure platforms that support large-scale AI training and inference workloads
- Improve reliability, scalability, and efficiency of systems operating at hyperscale
- Work on container orchestration, cluster scheduling, and workload isolation
- Optimize performance across compute, networking, and storage layers
- Build automation tools for infrastructure provisioning and operations (Infrastructure as Code)
- Collaborate with hardware, networking and ML teams to deliver end-to-end infrastructure solutions
Benefits
- Attractive compensation package, welfare benefits and developmental opportunities such as training and mentoring
- Open workspaces
- Involvement in new projects, developing processes/systems