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

"We put science to work!"

Savannah River National Laboratory (SRNL) is a multi-program laboratory applying state of the art science and practical, high-value, cost-effective solutions to complex technical problems to protect the nation. Located at the U.S. Department of Energy's (DOE) Savannah River Site (SRS) in Aiken SC, the laboratory develops and deploys innovative technologies to address some of the nation's environmental, energy, and national security challenges.

Battelle Savannah River Alliance (BSRA) is constantly assessing trends to provide the best possible benefits to our workforce. We also negotiate cost effective premiums that will meet the needs of our evolving workforce.

Some of the *Benefits offered to employees include:

*Benefits vary based upon employment status

• Highly competitive Medical, Dental, and Vision options including HSA options with company provided seed
• Short- & Long-Term Disability (company paid)
• Life Insurance Non-Contributary 1X salary (company paid)
• AD&D Non-contributary 1x salary (company paid)
• Savings & Investment plan:
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  • Qualified Non-Elective Company Contribution of 5% each pay period with immediate vesting
  • Company match 50 cents/dollar up to 8% (5 yrs. vesting in company match)
  
  
• Contributory Life Insurance up to 5x Salary with $1M Cap
• Contributory AD&D (employee, spouse and children)
• Paid Time Off
• Employee Assistance Plan
• SRNL offers a competitive relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions.

For more information about our benefits, working here, and living here, visit the "About" tab at www.srnl.doe.gov.

BSRA is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status. BSRA is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. Please email us at SRNLRecruiting@srnl.doe.gov with any questions regarding the hiring process or to request an accommodation.