Software Engineer Graduate (AI Compute) - 2027 Start (PhD)

What you'll do

• Design and build scalable, resilient container-based cluster management and orchestration systems.
• Architect GPU and AI accelerator infrastructure for cost-efficient, secure ML platforms.
• Develop production-ready inference solutions in collaboration with teams using LLM engines and open-source technologies.

What they ask for

• Completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Strong understanding of large-model inference, distributed and parallel systems, and/or high-performance networking.
• Hands-on experience building cloud or ML infrastructure, such as resource management, scheduling, request routing, monitoring, or orchestration.
• Knowledge of Docker and Kubernetes, and proficiency in Go, Rust, Python, or C++.

Nice to have

• Experience with large-scale cluster management, GPU orchestration, workload scheduling, or GPU programming.
• Familiarity with inference engines, public cloud ML platforms, and distributed ML systems.

Tools

Docker, Kubernetes, Go, Rust, Python, C++, vLLM, SGLang

AI focus

Build GPU-optimized infrastructure and systems for large-scale LLM inference and AI workloads.