Join Carnegie Mellon University’s SEI AI Division as a Senior Machine Learning Engineer. In this role, you will engineer solutions to support research into AI and ML vulnerabilities, focusing on building responsible and secure AI systems for government sponsors.
What You'll Do
- 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 and provide guidance on AI capabilities to government sponsors.
- Build machine learning models and systems using frameworks like TensorFlow, PyTorch, Torch, and Caffe.
- Conduct technical experimentation with modern and emerging ML frameworks and algorithms.
- Conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments.
- Collaborate with teams of developers, researchers, designers, and technical leads.
- Mentor and teach others to improve the overall technical capabilities of the Division.
What We're Looking For
- Comprehensive knowledge of machine learning.
- A track record of using well-established engineering practices to solve difficult problems.
- An understanding of how to convert research results into functioning prototypes or capabilities.
- Experience leading technical projects in novel areas with limited previous work to build upon.
- Strong written and verbal communication skills; able to convey complex technical ideas in layperson’s terms.
- Ample experience with publishing written or technical artifacts showcasing your work.
- Strong collaboration skills for working with colleagues and sponsors.
- Willingness to guide and mentor junior team members.
- A bachelor’s degree in computer science.
Nice to Have
- Previous experience in adversarial machine learning is desirable but not required.
Technical Stack
- TensorFlow, PyTorch, Torch, Caffe
- Python, C/C++, Java
Team & Environment
You'll be part of the Secure AI Lab within the SEI’s AI Division, consisting of machine learning research scientists, machine learning engineers, and software developers. The culture is creative, curious, energetic, collaborative, technology-focused, and hard-working, focused on bringing innovation to government organizations.
