Join Carnegie Mellon University (SEI AI Division) to engineer responsible, secure, and robust AI systems for government research and sponsors.

Identify and investigate emerging AI and AI-adjacent technologies
Define and refine processes, practices, and tools for working with AI
Design and build well-engineered prototypes of AI systems
Transition AI capabilities and provide guidance to government sponsors
Build machine learning models and systems using TensorFlow, PyTorch, Torch, and Caffe
Develop with modern programming languages including Python, C/C++, and Java
Work with data pipelines, ETL processes, and backend systems
Work with, extend, and implement state-of-the-art machine learning methods
Experiment with modern and emerging ML frameworks, methods, and algorithms across domains including computer vision, natural language processing, planning and scheduling, and robot control
Engineer safe, trusted, and reliable machine learning systems
Run rapid prototyping to demonstrate and evaluate technologies in relevant environments
Evaluate systems for performance and security
Test capabilities using novel testing and analysis techniques
Collaborate on teams with developers, researchers, designers, and technical leads
Work with researchers and government customers to understand challenges, needs, and solution directions
Improve the Division’s technical capabilities through mentoring and teaching, participating in design sessions, and sharing technical insights

Counter AI Research: Study threat models for AI/ML algorithms, understand AI behaviors, identify weak points, and design approaches to subvert AI/ML systems
AI and ML Algorithm Defense Research: Develop practical mitigations and defenses for observed attacks and evaluate defensive effectiveness
Applied Adversarial Machine Learning: Advance the state of the art by developing and transitioning adversarial ML capabilities to government sponsors

Comprehensive knowledge of machine learning
Previous experience in adversarial machine learning is desirable (not required)
Proven track record applying well-established engineering practices to difficult problems
Understanding of how to translate research results into functioning prototypes or capabilities
Experience leading technical projects in novel areas with limited prior work to build upon
Strong written and verbal communication skills, including the ability to explain complex concepts in layperson terms
Experience publishing written or technical artifacts showcasing work
Strong collaboration skills with colleagues and sponsors
Willingness to guide and mentor junior team members
Education and experience combination:
- Bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience
- OR MS in the same fields with eight (8) years of experience
- OR PhD in the same fields with five (5) years of experience
Subject to a background investigation and able to obtain and maintain an active Department of War security clearance
Willing to work onsite at SEI offices in Pittsburgh, PA or Arlington, VA 5 days per week
Willing to travel up to 25% of the time to locations outside of your home location

Machine Learning Engineer

Job Description