Senior AI/ML Security Architect & Tech Leader

RiseMe; Menlo Park (CA); On-site; USD 347,000 - 403,000; Full time

Job summary

Meta is seeking a Senior security-focused engineer to drive secure AI/ML frameworks across large-scale products. You will act as a senior individual contributor, shaping security strategies and leading multi-disciplinary teams across Product, Infrastructure, and Enterprise Engineering.

You will identify high-risk items, develop threat models, and guide secure-by-design practices for ML lifecycles, including frontier models.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Experience leading projects with industry-wide impact.
• Vast experience communicating and working across functions to drive solutions.
• Significant experience in mentoring/influencing engineers across organizations.
• Proven track record of planning multi-year roadmap.
• Experience in driving large cross-functional/industry-wide engineering efforts.
• 12+ years coding experience in C, C++, Java and/or C#.
• 12+ years experience building server applications.

Responsibilities

• Architect and implement security frameworks for large-scale AI/ML products and features.
• Lead cross-functional teams to develop security solutions and platforms for the company.
• Identify and mitigate security risks unique to AI/ML systems and frontier models.
• Communicate trade-offs to senior leadership to balance security and speed of innovation.

Skills

C/C++/Java/C#

Server applications

AI/ML security

Python

Threat modeling

Frontier AI models

Cross-functional collaboration

Education

Bachelor's degree in Computer Science/Engineering or equivalent

Advanced degree in CS or Security

Tools

TensorFlow/PyTorch

Job description

Meta is seeking a Senior security-focused engineer to drive secure AI/ML frameworks across large-scale products. You will act as a senior individual contributor, shaping security strategies and leading multi-disciplinary teams across Product, Infrastructure, and Enterprise Engineering.

You will identify high-risk items, develop threat models, and guide secure-by-design practices for ML lifecycles, including frontier models.