Robust AI Engineer

Requisition Id 12670 

Overview:  

As a U.S. Department of Energy (DOE) Office of Science national laboratory,Oak Ridge National Laboratory (ORNL) has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

The AI systems section in the National Security Sciences Directorate of Oak Ridge National Laboratory invites applications for professional researchers in robust machine learning.

The AI Systems section designs, develops, and delivers innovative research solutions that either apply or test applications of data science and machine learning for emerging areas of cyber security and automated analytic processing. Projects frequently involve collaboration across scientific fields, and result in publications, prototypes, and technology transfer to both government and commercial uses. Researchers from our section conduct basic and applied research at the state-of-the-art, mentor and teach, work on some of the most challenging problems, and participate in leadership research and development forums.

Major Duties/Responsibilities: 

Our organization seeks an innovative thinker with substantial machine learning skills to assist a diverse team with an expertise in evaluation, design, assessment, and development of robust and resilient machine learning algorithms. The position will work in teams of professional computer scientists, cybersecurity experts, mathematicians, software engineers to deliver innovative solutions and solve challenging problems.

The ideal candidate will be self-disciplined, have a strong work ethic, and an eagerness to tackle exciting research problems. A substantial formal education and/or experience with both deep and general machine learning, as well as the ability and desire to learn necessary concepts of the adversarial AI and robust learning is required.

The candidate will  support dissemination of results through presentations, posters, academic publications, and technical reports. They will take responsibility for subtasks requiring a study, analysis, interpretation and implementation of robust AI/ML methods, and  facilitate literature surveys, replication of the-state-of-the-art results, and conduct original research.

All team members deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• Requires a master’s degree in computer science, electrical engineering, mathematics, statistics, or a related field and two (2) years of relevant experience. An equivalent combination of education and experience may be considered.
• Experience with two or more of the following:
  • Python, especially machine and deep learning libraries,
  • Adversarial AI methods
  • Linux/Unix platforms,
  • LaTeX, and
  • Git

Preferred Qualifications:

• An understanding of the fundamental machine and deep learning methods;  numerical linear algebra; probability theory; algorithms; and mathematical analysis.
• Technical writing skills.
• Interpersonal communication skills.
• Ability to give clear and engaging presentations of research for both technical and non-technical audiences.
• Passion for continued learning and development of job-related skills.
• A desire to work in a team environment both learning from and teaching those with other backgrounds to facilitate interdisciplinary research.
• A proven record of technical research skills and the desire to apply these skills to the national security domain.
• Practical and theoretical knowledge of adversarial AI tools and methods.

Special Requirements:

Visa sponsorship is not available for this position.

Q clearance with SCI: This position requires the ability to obtain and maintain a Secret Compartmented Information (SCI) clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program.  In addition, due the SCI, you may also be subject to random polygraph testing.  

Benefits at ORNL:  

ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov or call 1.866.963.9545.

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This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.