Research Software Engineer, AI/ML – Virginia Tech

V T CORPORATE RESOURCE CTR; Blacksburg (VA); Hybrid; USD 110,000 - 130,000; Full time

Job summary

V T CORPORATE RESOURCE CTR at Virginia Tech is seeking a Research Software Engineer to build and maintain AI and machine learning infrastructure. This hands-on role involves deploying LLMs, optimizing ML platforms, and integrating AI into workflows, with an emphasis on collaboration with faculty and researchers.

The successful candidate will have a Master's degree in a relevant field and significant experience in deploying LLMs. The position is hybrid, requiring onsite work weekly, and offers a salary between $110,000 and $130,000.

Qualifications

• Master's degree in Computer Science, Computer Engineering, or related field required.
• Demonstrated experience with deploying LLMs in production environments.
• Experience with machine learning frameworks like PyTorch or Transformers.

Responsibilities

• Build and maintain AI and machine learning infrastructure.
• Deploy and optimize large language models and ML platforms.
• Lead workshops and training for effective AI use in research.

Skills

Deploying and managing Large Language Models

Machine learning frameworks (PyTorch, Transformers)

GPU computing

Linux system administration

Containerization technologies

Education

Master's degree in Computer Science or related field

Tools

CI/CD pipelines

Grafana

Prometheus

Job description

Research Software Engineer, AI/ML – Virginia Tech

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 advanced computing tools.

The Research Software Engineer, AI/ML builds and maintains our AI and machine learning infrastructure. You’ll deploy and optimize LLMs, set up ML platforms, and help researchers integrate AI into their workflows. This is a hands‑on role where you’ll tackle varied challenges across AI services and grow your skills alongside the team. You will work directly with faculty, Computational Scientists, and the rest of the ARC team to make AI tools accessible and useful for research. The role also involves leading workshops and training to help more people use AI effectively.

Please note: Sponsorship is not available for this position. This is a hybrid position that will require onsite work each week.

Required Qualifications

• Master’s degree in Computer Science, Computer Engineering, or closely related field required, or bachelor’s degree and extensive, progressive experience.
• Demonstrated experience deploying and managing Large Language Models in production environments.
• Demonstrated experience with machine learning frameworks such as PyTorch or Transformers for model development and deployment.
• Demonstrated experience with GPU computing in high-performance computing environments.
• Professional experience with Linux system administration.

Preferred Qualifications

• Experience with containerization technologies for scalable ML workload deployment.
• Experience designing and developing RESTful APIs or web services for AI/ML tools and platforms.
• Experience with LLM inference serving frameworks such as vLLM, SGLang, or llama.cpp for high-throughput, low-latency model deployment.
• Experience with CI/CD pipelines using git or similar version control workflows for automated testing and deployment.
• Experience with observability and monitoring tools (Grafana, Prometheus) for production systems.

Benefits

• Salary: $110,000 – $130,000
• Overtime: Exempt – Not eligible for overtime.
• Appointment Type: Regular.
• Additional Information: The successful candidate will be required to have a criminal conviction check.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.