AI Engineer – New College Graduate
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Job Description
New graduate AI engineers building Bitdeer’s full-stack AI cloud infrastructure. Developing cloud, Kubernetes, model-serving, and AI Agent platforms for globally distributed workloads.
Responsibilities:
- Develop 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
- Develop 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
- Develop distributed training, model fine-tuning, model deployment, inference acceleration, serverless inference, model APIs, model evaluation, and production-grade LLM and multimodal model-serving capabilities
- Develop 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
- Develop 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
- Start in one program area based on interview assessment and business needs
- Potentially rotate across different roles as part of career development
- Build infrastructure and platforms powering AI startups, research institutions, and global enterprises
Requirements:
- 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 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
- Strong ownership mentality, engineering discipline, and commitment to creating meaningful impact
- Ability to work in the United States, based on the US role locations
Benefits:
- Opportunities to rotate across different roles as part of career development
- Inclusive, respectful environment with open workspaces and an energetic, start-up spirit
- Opportunities to network with industry pioneers and enthusiasts
- Direct contribution and impact on the digital asset and AI computing industry
- Involvement in new projects and developing processes/systems
- Personal accountability, autonomy, rapid growth, and learning opportunities
- Training and mentoring
- Equal employment opportunities
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