AI Red Teamer

This is an AI/Consultant Role, below is the details.

Responsibilities:

• Red Teaming AI Models and Systems:
• Design and execute red teaming exercises to identify potential vulnerabilities in AI models and systems.
• Develop scenarios and simulate attacks to test the robustness and resilience of AI solutions.
• Collaborate with AI developers and engineers to provide feedback and recommendations for improvement.

Technical Assessments:

• Conduct thorough technical assessments of AI models and systems, focusing on responsible AI and governance practices.
• Evaluate controls and potential vulnerabilities related to bias, explainability, safety, and security.
• Prepare reports and presentations to communicate findings and recommendations to stakeholders.

Required Skills

• Proven experience in conducting technical testing and assessments for AI models and systems.
• Strong understanding of responsible AI practices and governance controls.
• Familiarity with AI-related risks, including bias, explainability, safety, and security.
• Proficient in AI and machine learning technologies and methodologies.
• Skilled in using red teaming tools and techniques.
• Ability to analyze complex systems and identify potential vulnerabilities.
• Excellent written and verbal communication skills.
• Ability to convey complex technical information to non-technical audiences.
• Ability to perform a consultant role for both internal teams and external clients.
• Strong interpersonal skills and the ability to work effectively in a team-oriented environment.

Preferred Skills

• Proven track record in managing or leading teams focused on Trusted/Responsible AI for both Traditional and Generative AI systems.
• Strong understanding of Responsible AI principles and their application in real world scenarios.
• Expertise in detecting and addressing algorithmic biases.
• Designing fair models for diverse datasets and use cases.
• Hands on experience with tools and techniques for explaining AI models (ex.SHAP, LIME).
• Knowledge of privacy preserving techniques such as differential privacy and federated learning.
• Experience in ensuring compliance with privacy laws and regulations (ex. GDPR, CCPA).
• Proficiency in quantifying and managing uncertainty in AI predictions.
• Understanding of adversarial attack methods and defense mechanisms.
• Ability to design robust systems that mitigate adversarial vulnerabilities.
• Experience in benchmarking both Traditional AI / Generative AI models across multiple AI domains.
• Familiarity with performance benchmarking, trade offs and optimization techniques.
• Computer Vision: Object detection, image segmentation, etc.
• NLP: Language models, text classification, summarization, etc.
• Generative AI: Assessment of LLMs, diffusion models, etc.
• Code Intelligence: code generation, bug detection, and refactoring.
• Environmental Impact: Estimation AI carbon footprints.
• Ability to communicate complex AI systems to non technical stakeholders.

Preferred Qualifications

• Master’s or PhD in Computer Science, AI, Data Science, or a related field.
• Certifications in Responsible AI, Ethical AI, or AI Governance.
• Hands on experience with AI auditing and regulatory compliance frameworks (ex.ISO 42001, NIST AI RMF, EU AI Act).