What We Do:
The SEI helps advance software engineering principles and practices and serves as a national resource in software engineering, computer security, and process improvement. The SEI works closely with defense and government organizations, industry, and academia to continually improve software-intensive systems. Our core purpose is to help organizations improve software engineering capabilities and develop or acquire the right software, defect free, within budget and on time, every time.
Machine Learning researchers at the SEI help our government and industry clients solve their problems using ML technology. In this role, you will work with our customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products. You'll get a chance to work with elite cybersecurity professionals and university faculty to build new technologies that will influence national cybersecurity strategy for decades to come. You will co-author research proposals, execute studies, and present findings to DoD sponsors and at academic conferences.
Our team works on a wide range of projects. Some of our current work includes developing metrics and experimental designs for large-scale cybersecurity research programs, researching human-in-the-loop machine learning, and building classifiers to identify security vulnerabilities in code. We have access to a wide variety of cyber-related data, including malware samples, netflow data, cybersecurity training runs and tests, incident tickets, and more. If you are a computer science or statistics major with an interest in cybersecurity, we want to hear from you!
- Enrolled in a degree granting program.
- Willingness to travel to various locations to support the SEI’s overall mission. This includes within the SEI and CMU community.
- You will be subject to a background check and must be eligible to work in the United States without Visa sponsorship.
Knowledge, Skills and Abilities:
- Coursework and/or projects in machine learning or statistics
- Familiar with at least one mathematical/statistical programming package (e.g., python numpy/scipy/pandas, R, MATLAB, etc.)
- Comfortable working in the Unix command line
- Familiar with at least one deep learning framework (e.g., TensorFlow, Caffe)
- Familiarity with machine learning techniques (e.g., K-means, SVM, neural networks)
- Solid communication skills (oral and written), particularly regarding technical communications with non-experts
- Coursework and/or projects in Natural Language Processing, Neural Networks, Optimization Theory, Graph Theory, or Computer Vision
- Deep understanding of statistical modeling techniques
- Software engineering skills
- Coursework in cybersecurity
Please visit “Why Carnegie Mellon” to learn more about becoming part of an institution inspiring innovations that change the world.
A listing of employee benefits is available at: www.cmu.edu/jobs/benefits-at-a-glance/.