Artificial Intelligence Machine Learning Lead at Leidos

Description

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers’ success. We empower our teams, contribute to our communities, and operate sustainable. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community. Our Mission, Vision, and Values guide the way we do business.

If this sounds like the kind of environment where you can thrive, keep reading!

The Digital Modernization Sector brings together our digital transformation and IT programs, allowing us to better serve our customers through scale and repeatability.

Your greatest work is ahead!

The mission of the DHS Chief Information Security Officer Directorate (DHS CISOD) is to support the Department’s implementation of all applicable regulatory requirements including the Federal Information Security Modernization Act of 2014 (FISMA), relevant Office of Management and Budget (OMB) Circulars, Executive Orders, Federal laws, directives, policies, and regulations. The DHS CISOD’s mission is to also provide the Department of Homeland Security (DHS) a secure and trusted computing environment. The DHS CISOD assists in ensuring Department compliance with information security requirements. Information security is an essential business function, critical to enabling DHS to conduct its operations and deliver service to the public.

We are seeking an Artificial Intelligence Machine Learning (AI/ML) Lead to join our team. As the AI/ML Lead, you will spearhead the exploration of cutting-edge AI frameworks, lead research on AI methodologies, and document the entire lifecycle of AI models—from creation to deployment and operation—while addressing the risks and vulnerabilities within each phase. You will play a crucial role in developing robust security strategies for AI/ML applications, ensuring compliance with industry standards, and mentoring security analysts and penetration testers.

Primary Responsibilities:

• Lead research into AI/ML frameworks, ensuring alignment with emerging trends and technologies.
• Document the entire lifecycle of AI models, focusing on risks and vulnerabilities during model creation, deployment, and operation.
• Develop security strategies and testing procedures tailored to AI/ML applications, including real-world attack scenario simulations.
• Mentor security analysts and penetration testers, providing knowledge and tools for AI/ML risk assessment.
• Collaborate with IT security teams to implement AI/ML best practices and ensure compliance with industry and regulatory standards

Qualifications:

• BS Degree and 12 - 15 years of experience.
• Expertise in documenting AI/ML lifecycle processes, identifying risks and mitigating vulnerabilities.
• Strong background in AI security, including the development of attack simulations and testing methodologies.
• Proven ability to lead teams and mentor professionals in AI/ML security techniques.
• GISP or SANS certification required
• Active Secret Clearance with eligibility to upgrade to Top-Secret/SCI.

Preferred Qualifications:

• Experience developing AI security policies and frameworks for federal government or highly regulated environments.
• Familiarity with AI/ML frameworks and methodologies, including secure deployment and operational practices.
• Strong knowledge of AI/ML model testing, bias detection, fairness, and ethical AI practices.
• Experience conducting security evaluations and training sessions for AI/ML applications.
• Expertise in regulatory compliance related to AI security, including industry standards

Original Posting Date:

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.