Research Software Engineer, AI/ML

Virginia Tech•Blacksburg, VA

13h•Hybrid

About The Position

Advanced Research Computing (ARC) provides Virginia Tech researchers with access to high-performance computing systems, data storage, visualization facilities, and expert support. We help faculty and students across all disciplines get the most out of HPC and advanced computing tools. The Research Software Engineer, AI/ML builds and supports the software that makes AI and machine learning accessible to our researchers. This is a hands-on, generalist role where you'll tackle varied challenges across AI services, grow your skills alongside the team, and progressively own our LLM infrastructure. You will work directly with faculty, Computational Scientists, and the rest of the ARC team to make AI tools useful for research. The role also involves leading workshops and training to help more people use AI effectively.

Requirements

Master's degree, or a combination of education, training, and progressive experience that equates to a Master's degree
Demonstrated professional experience working natively in a Linux environment (shell, scripting, package management, and system-level troubleshooting)
Demonstrated experience developing and maintaining software and/or web services
Experience with containerization technologies for deploying scalable workloads

Nice To Haves

Demonstrated experience deploying and managing LLMs in production, including GPU computing in HPC environments
Experience with LLM inference serving frameworks (vLLM, SGLang, llama.cpp) for high-throughput, low-latency deployment
Experience using or building AI-driven applications and agent workflows (e.g., tool-calling, orchestration, integration into existing services)
Experience with CI/CD pipelines, observability, and monitoring (Grafana, Prometheus) for production systems

Responsibilities

Builds and supports the software that makes AI and machine learning accessible to researchers.
Tackles varied challenges across AI services.
Grows skills alongside the team.
Progressively owns LLM infrastructure.
Works directly with faculty, Computational Scientists, and the ARC team to make AI tools useful for research.
Leads workshops and training to help more people use AI effectively.