Secure AI Engineer: Adversarial ML & Defense

Software Engineering Institute | Carnegie Mellon University; Pittsburgh (Allegheny County); On-site; USD 120,000 - 180,000; Full time

Job summary

Carnegie Mellon University, in the SEI AI Division, seeks a Machine Learning Engineer to advance secure AI systems for government sponsors. You will engineer solutions addressing vulnerabilities in AI/ML algorithms and build robust pipelines using TensorFlow, PyTorch, and modern languages such as Python, C/C++, and Java.

You will work on counter AI research, defense research, and applied adversarial ML, collaborating with researchers, developers, and sponsors to deliver practical, secure AI

Qualifications

• Comprehensive knowledge of machine learning and AI security concepts.
• Track record of applying engineering practices to solve hard problems.
• Ability to turn research into functioning prototypes or capabilities.
• Experience leading technical projects in new areas with limited prior work.
• Strong written and verbal communication skills.

Responsibilities

• Identify emerging AI and AI-adjacent technologies and assess applicability.
• Define and refine processes, practices, and tools for working with AI.
• Design and build prototypes of AI systems that are robust and secure.
• Transition AI capabilities to government sponsors with clear guidance.
• Mentor junior team members and collaborate across teams.

Skills

TensorFlow

PyTorch

Python

C/C++

Java

Data pipelines

Education

Bachelor’s degree in CS/Stats/ML or related (10 yrs)

MS in related field (8 yrs)

PhD in related field (5 yrs)

Tools

TensorFlow

Torch

Caffe

Job description

Carnegie Mellon University, in the SEI AI Division, seeks a Machine Learning Engineer to advance secure AI systems for government sponsors. You will engineer solutions addressing vulnerabilities in AI/ML algorithms and build robust pipelines using TensorFlow, PyTorch, and modern languages such as Python, C/C++, and Java.

You will work on counter AI research, defense research, and applied adversarial ML, collaborating with researchers, developers, and sponsors to deliver practical, secure AI