Data Scientist - Machine Learning and AI
Savannah River National Laboratory is seeking a highly motivated and self-starting AI (artificial intelligence) 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.
- 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
Typical Tools and Technologies:
- Python libraries: NumPy, pandas, SciKit-Learn, Pytorch, TensorFlow
- Data visualization tools: Plotly/Dash, Kibana, Matplotlib, Seaborn
- Machine learning frameworks: SciKit-Learn, Pytorch, TensorFlow
- Operating Systems: RHEL, Linux
- Batch processing tools: PBS, SLURM
- Version control systems: Git
- Agile development methodologies: Scrum, Kanban
- Others as the technology stack changes
Minimum Qualifications:
- 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 Plotly/Dash, Kibana, or similar tools
Preferred Qualifications:
- Experience with machine learning primitives and ability to choose the right approach for a given problem (e.g. decision trees, random forests, deep learning)
- Experience with natural language processing (NLP) techniques and libraries (e.g. NLTK, spaCy)
- Familiarity with containerization (e.g. Docker)
- Experience with cloud-based platforms (e.g. AWS, Azure)
- Certification in cybersecurity or a related field (e.g. CompTIA Security+, CISSP)
- Experience with proposal writing and research funding opportunities
- Masters Degree in Computer Science, Cybersecurity, or related field