Principal Cybersecurity Engineer ( AI/ML Open Source Security )

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Job Description:

At Discover, be part of a culture where diversity, teamwork and collaboration reign. Join a company that is just as employee-focused as it is on its customers and is consistently awarded for both. We’re all about people, and our employees are why Discover is a great place to work. Be the reason we help millions of consumers build a brighter financial future and achieve yours along the way with a rewarding career.

As a Principal Cybersecurity Engineer, you will have deep understanding of AI ML Security Risks, possess a strong background in application security engineering, and be eager to take on challenges related to AI-driven cybersecurity threats. We are looking for individuals who are adept in both traditional security approaches and the unique challenges posed by AI and ML technologies. This role will be a key role in application security engineering team, responsible for engineering support, development and delivery of AI/ML open source security initiatives, projects, or programs that have objectives associated with incorporating AI safety controls, designing and implementing processes to understand, measure, and improve the organization’s ability to protect open source AI/ML models, implement AI safety controls for responsible use of LLM (Large Language Model) applications.

Key Responsibilities
Develop and implement capabilities (process and tooling) to identify security risks in open source AI ML model evaluations, employing advanced ML and AI techniques.
Build and maintain scalable systems and processes to support open source AI safety evaluations and threat mitigation strategies.
Implement end-to-end LLM security risk management processes and automated protections.
Evaluate and assess open-source AI security libraries to build into enterprise AI open source security evaluation.
Provide engineering design and support in developing requirements for AI ML CI/CD pipeline
Deliver and integrate AI robustness, vulnerability, and stress testing capabilities with MLOps ecosystems.
Evaluate and assess open-source AI security libraries to build into enterprise AI stress testing and audit capabilities.
Establish and govern AI/ML and Generative AI application security standards.
Collaborating with multi-functional teams, including researchers, ML engineers, and security experts, to develop and implement best-in-class security solutions for AI systems.

Minimum Qualifications

At a minimum, here’s what we need from you:

• Bachelors – Computer Science,  Engineering, Informatics, Information Security, Information Technology or related

• 6+ years – Information Security, Application Security, Security Engineering or related

Internal applicants only: technical proficiency rating of proficient on the Dreyfus engineering scale

Preferred Qualifications

Bonus Points If You Have:

• Strong knowledge of AI Risk Management frameworks and Trustworthy AI practices.

• Hands-on experience with applying statistics, machine learning algorithms (DNN, NLP), big data, and data science toolkits. Hands-on experience designing, implementing, and operationalizing high performant AI/ML pipelines and writing production code.

• Hands-on experience with deploying and operationalizing AI/ML models to public cloud environments.

• Hands-on experience evaluating open-source ML tools, frameworks, and libraries.

• Hands-on experience with commonly used data science programming languages, packages, and tools.

• Hands-on experience with MLOps, DevOps, DataOps and API integrations.

• Hands-on experience with AI/ML technologies, including proficiency in Python, Rust, Go, and ML frameworks like TensorFlow, PyTorch, Keras.

• Demonstrated experience in red-team and penetration testing engagements.

• Excellent communication skills, with the ability to articulate complex technical findings to diverse teams.

External applicants will be required to perform a technical interview.

What are you waiting for? Apply today!

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