Data Scientist - Machine Learning & AI, Intermediate

About the role

Savannah River National Laboratory (SRNL) is seeking a highly motivated and self-starting AI and machine learning researcher to join our team in creating and maintaining large-language model research tools, especially for cybersecurity data. The successful candidate will have strong experience in Python, AI, and cybersecurity, with a focus on developing and maintaining high-quality code using unit testing, continuous integration, and deep learning models and libraries. The ideal candidate will be a solid researcher (PhD preferred), an independent worker, a good communicator, and a team player with a strong ability to write and document his or her work.

Responsibilities

• Develop and maintain large-language model research tools for cybersecurity data using Python, Huggingface models, and Pytorch libraries or other equivalent state-of-the-art technology
• Design and implement unit tests and continuous integration pipelines to ensure high-quality code
• Collaborate with team members to develop and maintain research tools and software applications
• Write and maintain technical documentation for research tools and software applications
• Participate in code reviews and contribute to the improvement of the overall codebase
• Develop and maintain strong understanding of cybersecurity concepts and threats
• Collaborate in writing proposals for external sponsors, Laboratory Directed Research and Development (LDRD) projects, and other funding opportunities
• Stay up-to-date with the latest developments in AI, cybersecurity, and large-language models

Requirements

• Bachelor's degree in Computer Science, Cybersecurity, or related field and 4-6 years of experience in software development, preferably in a research environment
• For ability to obtain and maintain a security clearance, US Citizenship is Legally Required
• Strong experience in Python programming, including experience with AI and machine learning libraries (e.g. Pytorch, TensorFlow, scikit-learn)
• Experience with deep learning models and libraries, particularly Huggingface, Pytorch, etc.
• Strong understanding of cybersecurity concepts and threats
• Experience with unit testing and continuous integration (e.g. Jenkins, GitHub, or others)
• Excellent communication and teamwork skills
• Ability to write and document technical work
• Experience with version control systems (e.g. Git)
• Familiarity with Agile development methodologies
• Self-motivated and able to work independently
• Experience with Red Hat Enterprise Linux (RHEL) or similar Linux distributions
• Experience with batch processing tools such as PBS or SLURM
• Familiarity with data engineering and curation principles and practices
• Experience with data visualization tools such as Plot