Leidos

Compensation

Full Description

Job Description: • Develop and implement enterprise-scale Responsible AI systems and governance frameworks, ensuring they meet the ethical, performance, and security requirements for mission-critical applications. • Contribute to the architecture and implementation of a centralized 'Responsible AI Framework' to ensure compliance, manage model access, and provide a unified interface for governance and risk management. • Implement and manage robust monitoring systems to track model performance, fairness, bias, and ethical compliance, and to optimize the cost-effectiveness of AI systems in production. • Work closely with principal engineers, data scientists, and systems architects to translate strategic designs into hardened, production-grade solutions that embed fairness, accountability, and transparency principles. • Establish and maintain robust AI governance frameworks and guardrails to ensure data integrity, filter inputs/outputs, prevent bias, mitigate deployment risks, and protect against adversarial attacks. • Apply and promote software engineering best practices, including robust version control, comprehensive automated testing, and mature CI/CD processes for AI systems. • Stay current with industry trends in Responsible AI, Explainability (XAI), operational AI, and MLOps to continuously evolve the team's capabilities and technical implementation. Requirements: • A Bachelor's degree in Computer Science, Engineering, or a related quantitative field with 12+ years of professional experience, OR a Master's degree with 10+ years of relevant experience. • Demonstrated programming proficiency in Python and hands-on experience with major ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Experience with software engineering best practices and tools, including version control, automated testing, and CI/CD pipelines. • Solid understanding of the full machine learning lifecycle, from data preparation and model training to deployment and monitoring. • A strong understanding of Responsible AI principles, ethical AI practices, and techniques for bias detection and mitigation. • An understanding of cybersecurity principles as they apply to AI systems, including threat modeling and vulnerability assessment. • Must be a U.S. Citizen and have the ability to obtain and maintain a U.S. security clearance. Benefits: • competitive compensation • Health and Wellness programs • Income Protection • Paid Leave • Retirement