AI Engineering – New College Graduate 2027

Bitdeer AI, a full-stack AI cloud provider (AI Data Center, IaaS, PaaS, MaaS) under Bitdeer Technologies Group and a preferred NVIDIA Cloud Partner, is engineered to power the AI of tomorrow.

With the group’s 3 Gigawatts of power capacity deployed and under development globally, Bitdeer holds a decisive advantage in the AI era: the massive energy, physical infrastructure, and compute foundation required to run intelligence at global scale. Operating across strategic international hubs, including the United States, Singapore, and Europe, we build on one core promise: One Cloud, Infinite Possibilities.

We are looking for key talents to develop in the following areas:

• →Cloud Service Platform: Development of large-scale, highly available AI cloud services, including GPU virtual machines, bare-metal services, container services, cloud networking, storage, billing, monitoring, security, and multi-region resource management.
• →Kubernetes Service Platform: Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads.
• →AI Model Training and Inference Platform: Development of distributed training, model fine-tuning, model deployment, inference acceleration, serverless inference, model APIs, model evaluation, and production-grade LLM and multimodal model-serving capabilities.
• →AI Agent Platform: Development of enterprise AI Agent platforms, including Agent building, workflow orchestration, tool integration, retrieval-augmented generation, memory systems, sandbox execution, multi-Agent collaboration, evaluation, observability, security, and large-scale Agent runtime infrastructure.
• →Advanced AI Systems: Development of GPU resource scheduling, distributed systems, high-performance networking, cloud-native infrastructure, MLOps and LLMOps platforms, AI application marketplaces, and automated operation systems for large-scale AI infrastructure.

Career Opportunities within the Program:

• →Cloud Platform Engineering
• →AI Operations, MLOps & Site Reliability Engineering
• →MaaS, Model Serving & AI Training Infrastructure
• →AI Agent & Application Engineering
• →AI & Cloud Security Engineering
• →AI Research

Successful candidates will start in one of the above areas based on the interview assessment and business needs. Opportunities to rotate across different roles will also be provided as part of career development.

• →A culture that values authenticity and diverse perspectives.
• →An inclusive, respectful environment with open workspaces and an energetic, start-up spirit.
• →A fast-growing company with opportunities to network with industry pioneers and enthusiasts.
• →The ability to contribute directly and make an impact on the future of the digital asset and AI computing industry.
• →Involvement in new projects and in developing processes/systems.
• →Personal accountability, autonomy, rapid growth, and learning opportunities.
• →Attractive benefits and development such as training and mentoring.

Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, color, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.

• Fresh graduates (Bachelors, Masters, PhD) from all disciplines and/or candidates with up to 2 years of related work experience.
• Strong programming ability in one or more languages, including Go, Python, C++, Java, Rust, or related technologies.
• Experience with Kubernetes, Docker, Helm, Terraform, OpenStack, Prometheus, Grafana, Argo, Istio, PostgreSQL, Redis, message queues, distributed storage, or other cloud-native technologies is highly preferred.
• Experience in developing or operating large-scale cloud platforms, Kubernetes platforms, AI training platforms, inference platforms, or Agent platforms is highly preferred.
• Deep enthusiasm for cutting-edge AI infrastructure, cloud-native technologies, and building large-scale, globally distributed systems.
• Proven achievements in academics, engineering projects, top-tier publications, open-source contributions, or programming/algorithm competitions.
• A strong ownership mentality, engineering discipline, and a commitment to creating a meaningful impact early in your career as we build the foundation for next-generation AI.