AI Research Engineer: NLP, LLMs & AI Apps for Security

Auburn; Washington (District of Columbia); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Life-Changing Impact

Culture of Excellence

Generous benefits

Southern charm

Job summary

Auburn University’s Charles D. McCrary Institute seeks a Research Engineer with AI/ML and NLP experience to advance applied research and national security initiatives in Washington, D.C. The role emphasizes model development, deployment, and collaboration with AI labs across projects.

Responsibilities include building AI-powered apps, leveraging LLMs and RAG, and contributing to grant proposals while supporting data pipelines and cloud deployments in AWS or MS Azure.

Qualifications

• Bachelor's degree in Engineering relevant to the area of research.
• Experience with AI/ML development, NLP, and model deployment is preferred.
• Familiarity with cloud environments (AWS or Azure) and data pipelines.

Responsibilities

• Understand NLP model training, fine-tuning, and evaluation.
• Use LLMs, prompt engineering, and Retrieval-Augmented Generation (RAG).
• Utilize and integrate web service APIs and build AI-powered applications.
• Deploy and monitor AI models and data pipelines.
• Work with SQL and NoSQL databases for data prep and querying.
• Collaborate with AI labs and researchers across projects.
• Serve as co-principal investigator on research proposals and funded efforts.
• Travel to Huntsville and Auburn may be required.

Skills

NLP

LLMs

AI/ML development

Systems engineering

Cloud: AWS/MS Azure

Data pipelines

Education

Bachelor's degree in Engineering relevant to the area of research

Job description

Auburn University’s Charles D. McCrary Institute seeks a Research Engineer with AI/ML and NLP experience to advance applied research and national security initiatives in Washington, D.C. The role emphasizes model development, deployment, and collaboration with AI labs across projects.

Responsibilities include building AI-powered apps, leveraging LLMs and RAG, and contributing to grant proposals while supporting data pipelines and cloud deployments in AWS or MS Azure.