Senior Artificial Intelligence/ Machine Learning Security Engineer

Key Skills

Aartificial intelligence, API, Big Data Technology, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, DataOps, DevOps, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Natural Language Processing (NLP)

Job Description

How will you make an impact in this role?

Organizational Context: Executes end-to-end information security, IT risk management processes and automated capabilities that promote trustworthy AI practices. Works across many organizations, both internal and external, to meet business needs and compliance goals. Leads cross department initiatives, covering a wide range of business/technical functions.

Focus: Responsible for the development and or delivery of AI/ML security initiatives, projects, or programs that have objectives associated with incorporating AI safety controls, adversarial robustness, and stress testing of AI/ML systems Responsible for designing and implementing processes to understand, measure, and improve the organization’s ability to protect AI/ML models, implement AI safety controls for responsible use of LLM (Large Language Model) applications.

 Key Responsibilities

• Implement secure model development life cycle practices with automated white box and black box assessments for AI/ML models.
• 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.
• Implement end-to-end LLM security risk management processes and automated protections.
• Incorporate machine learning models into diverse application security tooling and processes.
• Support production deployments of AI/ML safety systems using cloud-native packaging and deployment techniques suchas containers, serverless, CI/CD and APIs.
• Establish and govern AI/ML and Generative AI application security standards.
• Provide production support and operations for AI/ML security systems.
• Manage cloud deployments and automation frameworks in cloud for AI/ML security systems.

Minimum Qualifications

• Bachelor's Degree in Data Science, Statistics, Computer Science or Software Engineering
• 3+ years experience with Machine Learning Application Development
• 3+ years of software engineering experience

Preferred Qualifications:

• Master's Degree - Data Science, Statistics, Computer Science, or Software Engineering 
• Machine Learning Operation Professional Certifications
• Strong knowledge of Adversarial Robustness techniques and tools for machine learning 
• 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 workload management.
• Hands-on experience with Cloud architecture, design, implementation, and operations.
• Demonstrated peer reviewed journal publications, conference presentations, open-source contributions, or similar activities.

Salary Range: $110,000.00 to $190,000.00 annually + bonus + benefits

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:

• Competitive base salaries 
• Bonus incentives 
• 6% Company Match on retirement savings plan 
• Free financial coaching and financial well-being support 
• Comprehensive medical, dental, vision, life insurance, and disability benefits 
• Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need 
• 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy 
• Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) 
• Free and confidential counseling support through our Healthy Minds program 
• Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.

We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.

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