AI Platform Research Scientist I/II

Georgia Institute of Technology; Atlanta (GA); On-site; USD 53,000 - 110,000; Full time

Job summary

Georgia Tech’s Office of Information Technology invites applications for a Research Software Engineer with the PACE team in Atlanta. You will build and operate AI-centric platforms to support GT researchers, focusing on scalable, secure AI/ML workflows and tools like JupyterHub and MLflow.

You will collaborate with Platform and CI teams to deliver reliable, reproducible research infrastructure and contribute to software that accelerates scientific discovery.

Qualifications

• Bachelor’s degree in CS or related field is required.
• Advanced degree or significant experience in research software is preferred.
• Experience building/operating AI-centric platforms and workflows is desirable.
• Strong communication skills for collaboration with researchers are essential.

Responsibilities

• Build and operate AI-centric platforms (e.g., JupyterHub, MLflow) for multi-tenant research use.
• Improve performance, scalability, and reliability of AI services in production.
• Enable repeatable ML workflows and model deployment patterns.
• Maintain and evolve the central software stack with containerized tooling.
• Produce clear documentation and runbooks for operations.
• Collaborate with Platform and CI teams to support GT researchers.
• Publish results and contribute to open research software as appropriate.
• Support deployment of AI applications and workflows on PACE systems.

Skills

Python

Shell scripting

GPU/HPC

Linux

CI/CD

Research collaboration

Education

Bachelor's in Computer Science or related

Master's/PhD in related field

Tools

Docker

Apptainer

Podman

Spack

EasyBuild

JupyterHub

MLflow

Job description

Georgia Tech’s Office of Information Technology invites applications for a Research Software Engineer with the PACE team in Atlanta. You will build and operate AI-centric platforms to support GT researchers, focusing on scalable, secure AI/ML workflows and tools like JupyterHub and MLflow.

You will collaborate with Platform and CI teams to deliver reliable, reproducible research infrastructure and contribute to software that accelerates scientific discovery.